ObjectiveDonkey hide is the sole legally designated raw material for the preparation of the traditional Chinese medicine Ejiao. The quality stability of donkey hide during preservation directly determines the efficacy and safety of Ejiao. This study focuses on the dynamic succession of microbial communities during the preservation of donkey hides from different origins, aiming to clarify the correlation between microbial biodiversity difference and the degradation profiles of hide collagen and critical biochemical components, thereby providing a theoretical foundation for developing targeted preservation strategies based on microbial regulation. MethodsDonkey hides originating from four different regions were subjected to an accelerated microbial aging assay to simulate the spoilage process. The microbial community succession was analyzed using high-throughput sequencing. Microstructure changes and pore structure characteristics were assessed by scanning electron microscopy and mercury intrusion porosimetry, respectively. Additionally, the content of major components, including lipids, proteins, and sugars were determined by biochemical methods. ResultsAfter 96 h of aging, the collagen fiber structure in Africa donkey hides (ADH) exhibited significant degradation and collapse, followed by Xinjiang donkey hides (XDH). Instead, the microstructure of Dong’e black donkey hides (DDH) and Peru donkey hides (PDH) remained relatively intact. The porosities of DDH, XDH, PDH, and ADH increased from 27.9%, 15.7%, 30.3%, and 46.2% to 36.5%, 52.6%, 42.8%, and 57.7%, respectively, during the aging process, which suggested that the originally compact fiber structure was disrupted by microbial aging. Fourier transform infrared spectrometer analysis revealed the amide bands in XDH exhibited relatively weak intensity, and no collagen amide I band was observed in ADH. Meanwhile, the lipid and protein contents decreased in all four types of donkey hides, indicating that these components served as the primary nutrient sources for the growth of microorganism. Notably, the most severe collagen degradation was observed in XDH and ADH. A substantial increase was detected in the total soluble sugar in PDH aging solution and hydroxyproline in the ADH aging solution, respectively. These results indicated that donkey hides exhibit distinct patterns of structural degradation and nutrient utilization. Furthermore, the viable cells number of donkey hides increased sharply after 48 h of aging. Metagenomic analysis revealed that the relative abundance of Euryarchaeota in ADH, PDH and XDH declining from initial 93.19%, 97.73% and 30.08% to 0.79%, 1.43% and 0.02% after 96 h, respectively. Conversely, a significantly increase was observed in the abundance of Bacillota, with a marked increase in ADH, peaking at 92.75%. Additionally, the abundance of Pseudomonadota in PDH increased from 0.10% to 87.84%, suggesting that Bacillota and Pseudomonadota may be key factors exacerbating donkey hide spoilage. Unlike the other three types of donkey hides, the dominant bacterial phylum in DDH shifted from Pseudomonadota to Bacteroidota, characterized by a substantial abundance increase of Bacteroidota from 0.13% to 44.22%. ConclusionRegional variation in origin significantly influence the microbial aging of donkey hides, leading to distinct patterns of structural deterioration and differential nutrient utilization. Therefore, implementing origin-specific preservation strategies, through the precisely controlling environmental factors to suppress harmful phyla such as Bacillota and Pseudomonadota, is crucial for enhancing the storage quality of donkey hides.

Mitochondrial biogenesis represents a promising therapeutic target in triple-negative breast cancer (TNBC) due to its essential role in cancer cell metabolism and survival. The natural compound γ-Elemene exhibits potent anti-tumor activity, but its effects on mitochondrial regulation in TNBC remain unclear. In this study, we demonstrate that γ-Elemene induces dose-dependent cytotoxicity in MDA-MB-468 and HCC1806 TNBC cells while significantly impairing mitochondrial function, as shown by reduced membrane potential, oxidative phosphorylation capacity, and ATP production. γ-Elemene treatment markedly suppressed mitochondrial biogenesis, decreasing mitochondrial DNA content and downregulating key mitochondrial genes and proteins. These effects were associated with reduced expression of the master regulators NRF1 and TFAM, but independent of PGC-1α expression levels.Mechanistically, γ-Elemene upregulated the acetyltransferase GCN5, leading to enhanced PGC-1α acetylation. This upregulation occurs primarily through increased GCN5 transcription. Genetic ablation of GCN5 completely reversed γ-Elemene-induced PGC-1α acetylation and restored mitochondrial biogenesis and cell viability, establishing a critical role for GCN5 in mediating these effects. Our findings reveal a novel mechanism whereby γ-Elemene disrupts mitochondrial function in TNBC through GCN5-mediated PGC-1α acetylation, providing new insights into its anti-cancer properties and potential therapeutic applications against TNBC.

Owing to its inherent advantages—such as being non-destructive, rapid, highly molecule-specific, and minimally interfered with by moisture—Raman spectroscopy has been widely adopted in the fields of skin barrier function assessment, monitoring the transdermal penetration of active cosmetic ingredients, and the identification and quality control of cosmetic products. Despite these strengths, the practical application of this technique faces a significant bottleneck: the strong fluorescence background generated by endogenous skin components and exogenous cosmetic additives. Endogenous skin substances, such as structural proteins (e.g., collagen and elastin), metabolic coenzymes (e.g., nicotinamide adenine dinucleotide), and pigments (e.g., melanin), together with exogenous cosmetic constituents like organic colorants, chemical sunscreens, and fragrances, often possess strong absorption and emission characteristics. When excited by lasers, these components produce a fluorescence background that can be 10⁶ to 10⁸ times stronger than the Raman scattering signals, effectively masking the inherently weak vibrational fingerprint information. In recent years, driven by the rapid development of optoelectronic hardware and artificial intelligence algorithms, fluorescence suppression strategies have evolved from isolated, single-method approaches into comprehensive, multi-level synergistic systems. These systems are categorized into three distinct tiers: sample preparation, signal acquisition, and data processing. At the sample preparation level, techniques such as photobleaching and surface-enhanced Raman spectroscopy (SERS) are employed to eliminate or bypass the generation of fluorescence at the source. At the signal acquisition level, instrumental improvements—including the use of long-wavelength near-infrared excitation (typically 785 nm or 1 064 nm), confocal spatial filtering, and shifted excitation Raman difference spectroscopy (SERDS)— are utilized to physically isolate Raman signals from the fluorescence background. Furthermore, at the data processing level, numerical baseline correction methods such as polynomial fitting, penalized least squares (e.g., airPLS, arPLS), wavelet transform, and derivative algorithms are increasingly integrated into the analytical pipeline to extract Raman spectral features from mixed signals without increasing hardware costs or acquisition time. This review provides a systematic categorization and critical evaluation of these fluorescence suppression methods, detailing their underlying principles, technical advantages, and inherent limitations in diverse experimental setups. By focusing on critical application scenarios—including skin barrier assessment, percutaneous absorption monitoring, the routine quality control of cosmetics, and the emerging field of portable on-site detection—this paper explores the current state of technique selection and optimization. Finally, the article discusses future development trends, emphasizing the necessity of constructing adaptive, tiered suppression strategies, developing intelligent and automated data processing algorithms, and promoting the integration of portable, multi-modal diagnostic devices. The objective of this review is to provide a comprehensive technical reference to facilitate the transition of Raman spectroscopy from a specialized laboratory tool into a routine, robust analytical platform for advancements in skin science and cosmetic research.

Objective To analyze the genomic characteristics of Legionella pneumophila (L. pneumophila) isolated from industrial circulating cooling water in workplace. Methods A total of 20 L. pneumophila strains isolated from industrial circulating cooling water collected from eight chemical enterprises were selected as the research subjects. Whole-genome sequencing was performed on the strains, followed by multilocus sequence typing (MLST), whole-genome single nucleotide polymorphism analysis, virulence factor profiling, and antibiotic resistance gene detection. Results The dominant MLST typing among the 20 L. pneumophila strains was ST2. Serogroup 1 (Lp1) strains exhibited high genetic diversity. Strains from different enterprises showed substantial genomic diversity, suggesting possible inter-enterprise dissemination. Each isolate harbored 175-295 virulence genes; among them, virulence genes were identified, and 139 genes were detected in all the 20 strains. These genes primarily included those related to the Dot/Icm type Ⅳ bacterial secretion system, flagellar synthesis and motility, and type Ⅳ pili. The number of virulence genes carried by L. pneumophila strains of different ST types differed (P<0.01), with unidentified sequence types harboring more virulence genes than other STs (P<0.01). A total of four resistance genes were predicted, including aminoglycoside phosphotransferase-encoding gene APH(9)-Ia, carbapenemase-encoding gene OXA-29, and efflux pump genes-encoding genes LpeA and LpeB, with detection rates of 100.00%, 100.00%, 10.00%, and 10.00%, respectively. These genes may confer resistance to cephalosporins, penicillins, and aminoglycosides, and all strains were multidrug resistance. Conclusion L. pneumophila isolated from industrial recirculating cooling water exhibits high genetic diversity, strong pathogenicity, and significant multidrug resistance potential.

ObjectiveTo address the key challenges in breast electrical impedance tomography (EIT) reconstruction including the severe ill‑posedness of the inverse problem, limited measurement information from the electrodes, low contrast of small lesions, as well as the common drawbacks of traditional reconstruction methods such as boundary blurring, low spatial resolution, and weak small-target detection capability, and to overcome the limitations of existing deep learning approaches namely low training efficiency, insufficient physical consistency, and substantial information loss during the low‑to‑high dimensional mapping process, this study proposes a multi‑scale attention and dynamic sparse mask fusion network (MADS‑Net). The proposed method aims to enhance high‑resolution reconstruction accuracy, small-lesion detectability, noise robustness, and computational efficiency in breast‑screening-oriented EIT, thereby providing a feasible solution for the application of EIT in breast functional imaging. MethodsThe proposed network adopts a strategy of “locate first, reconstruct later”. It realizes adaptive allocation of computational resources through a dynamic mask module, alleviates information loss in the low-to-high dimensional mapping process via a multi-scale attention mechanism, and embeds physical constraints to improve the physical rationality of reconstruction results. The performance of the proposed method was validated through systematic numerical simulations, agar phantom experiments, and porcine tissue experiments. Comparisons were made with mainstream methods including the Gauss-Newton algorithm, convolutional neural networks, U-Net, and Deep D-Bar. The image correlation coefficient (ICC), root mean square error (RMSE), and peak signal-to-noise ratio (PSNR) were adopted as quantitative evaluation metrics. Furthermore, lesion‑level evaluation metrics were introduced to assess the capability of different methods in reconstructing abnormal target boundaries and small‑sized target regions. ResultsExperimental results demonstrate that MADS-Net outperforms all comparison methods across all test scenarios. In numerical simulations, it achieves higher accuracy in target morphology and spatial location recovery as well as better background suppression. In agar phantom experiments, its detection and imaging reliability for small targets is significantly superior to the comparison methods. In porcine tissue experiments, the model maintains good generalization performance and can adapt to complex biological tissue imaging scenarios. Quantitative results show that MADS-Net achieves an average ICC of 0.917 6±0.048 8, an RMSE as low as0.060 6±0.031 6, and a PSNR of (23.893 9±2.685 3) dB. It successfully detects tiny targets as small as 5 mm within a 100 mm diameter sensing field, reduces the total training duration by 23.5% compared with the baseline method, and maintains stable reconstruction performance even under strong noise interference. ConclusionThe results demonstrate that MADS-Net achieves favorable EIT reconstruction performance in numerical simulations, agar phantom experiments, and porcine tissue experiments, even under common practical imaging challenges including low signal-to-noise ratio and blurred tissue boundaries. This study provides a methodological reference for further research on EIT in breast-screening-related scenarios and other medical functional imaging tasks, and also offers a low-cost, radiation-free alternative for breast lesion screening that aligns with the clinical demand for non-invasive diagnostic tools. It should be noted that real clinical breast data have not yet been used for validation in this study, and the clinical applicability of the proposed method requires further investigation. Future work will prioritize collecting multi-center real clinical breast datasets, and further optimize the model’s generalization ability to adapt to individual differences in breast tissue composition to promote its clinical application.

Chronic post-dissection aortic aneurysms (PDAAs) are severe long-term complications following surgical or medical conservative management of aortic dissection, primarily caused by persistent perfusion of the residual false lumen. The persistent patency of the residual false lumen is the key pathological mechanism leading to adverse distal aortic remodeling, which can result in progressive aortic dilation, increased risk of rupture, and elevated reintervention requirements, significantly affecting patients' long-term prognosis. This article reviews the latest research progress on assessment methods, influencing factors, and intervention strategies for distal aortic remodeling in PDAAs, aiming to provide reference for clinical decision-making.

Objective To investigate the effect of pseudogene GTF3AP2 in erythroid differentiation.Methods The published high-throughput RNA sequencing(RNA-seq)data were analyzed to identify the functional pseudogene GTF3AP2,which may play a role in erythropoiesis.The endogenous expression of GTF3AP2 was inhibited by shR-NA in CD34+hematopoietic stem/progenitor cells to assess the colony-forming ability through colony-forming assay.Flow cytometry analysis was applied to detect changes in the ratio of erythroid/megakaryocytic progenitor cells.Ad-ditionally,the role of GTF3AP2 in erythroid differentiation was determined through transcriptome sequencing,which revealed alterations at the cellular and molecular levels following the knockdown of GTF3AP2.Results Com-pared with the sh-EV group,knockdown of GTF3AP2 resulted in a significant increase in cell expansion,character-ized by a significant rise in the number of colony-forming unit erythroid cells(P＜0.001),an increase in the proportion of CD71+CD235a+erythroid precursors(P＜0.01),and a decrease in the proportion of CD71-CD235a+mature erythrocytes(P＜0.05).Furthermore,there was a significant reduction in the expression of key erythroid dif-ferentiation genes,including KLF1,HBB,GYPA,EPOR and TFRC.Conclusions Knocking down of GTF3AP2 promotes the expansion of erythroid precursor cells and inhibits erythroid maturation,suggesting that GTF3AP2 plays a regulatory role in erythroid differentiation.

Organophosphorus nerve agents are the most threatening chemical warfare agents and terrorist agents.The number of nerve agents and their related chemicals involved in the verification of Chemical Weapon Convention(CWC)exceeds ten million,with the majority being isomers.Accurate structural identification of these chemicals has always been one of the challenges in CWC related verification analysis.In this work,a total of 17 kinds of alkyl phosphonate isomers and structural analogs from 5 groups were designed and synthesized,and then analyzed by gas chromatography-mass spectrometry(GC-MS)and gas chromatography-infrared spectroscopy(GC-FTIR).The spectra of isomers or structural analogs obtained from two techniques as well as the structural information provided therein were compared and analyzed.The results showed that for isomers or structural analogs with similar MS spectra,FTIR spectra could provided more structural fingerprint information of compounds and had advantages in confirming structures.Combined with the excellent separation ability of GC,GC-FTIR can be used to assist GC-MS in the structural confirmation of alkyl phosphates,achieving rapid and accurate identification of isomers or structural analogues.

Objective:To summarize the clinical characteristics of elderly patients with stage Ⅰ diffuse large B-cell lymphoma (DLBCL) and analyze the factors associated with prognosis.Methods:A case series study was conducted by retrospectively collecting clinical data from patients aged over 60 years with newly diagnosed stage Ⅰ DLBCL across 20 medical centers in Jiangsu Province, China, between June 2010 and April 2023. The involved site, classification and treatment plan were summarized. The primary endpoints were progression-free survival (PFS) and overall survival (OS). Statistical analyses were performed using the Kaplan-Meier method, and Cox regression model.Results:The study included 255 patients with a median age of 69 years, of whom 130 (51.0%) were male, 66 (25.9%) were aged ≥75 years and 26 (10.1%) had a high Charlson Comorbidity Index (CCI) score of ≥2. Extranodal involvement was observed in 163 (63.9%) patients, with the stomach (37.4%, 61/163), intestine (19.0%, 31/163), testes (11.0%, 18/163), and breast (7.4%, 12/163) being the most frequently affected sites. The non-germinal center B-cell (non-GCB) subtype was prevalent in 63.7% of patients (142/223), with no significant difference between the nodal and extranodal groups ( P=0.681). Furthermore, 73.9% (184/249) and 11.7% (29/249) of patients received the R-CHOP (rituximab, cyclophosphamide, doxorubicin, vincristine, prednisone) and R-miniCHOP regimen, respectively. The overall 3-year PFS rate was 81.5%, and the 3-year OS rate was 85.6%. Patients aged ≥75 years ( HR=2.910, 95% CI 1.565-5.408, P=0.001) and/or with a CCI score ≥2 ( HR=2.324, 95% CI 1.141-4.732, P=0.020) had a significantly poorer PFS. Incorporating age ≥75 years and CCI score ≥2 into the stage-modified international prognostic index (sm-IPI) can better stratify the prognosis of elderly patients with stage Ⅰ DLBCL. The 3-year PFS rate was 48.7% in the high-risk group versus 85.7% in the low-risk group ( P<0.001). Conclusions:Our findings show that the elderly patients with stage Ⅰ DLBCL were predominantly characterized by extranodal involvement (particularly in the stomach and intestinal tract) and non-GCB subtype. Age ≥75 years and CCI ≥2 were identified as independent prognostic factors. The newly established sm-IPI-75-CCI incorporating these factors demonstrated superior prognostic discrimination compared to conventional risk assessment systems.

Non-alcoholic fatty liver disease(NAFLD)is a chronic liver disease caused by excessive lipid accumulation in the liver.Its incidence rate is increasing year by year and has become an increasingly serious public healthy problem.The pathogenesis of NAFLD is complex and has not been fully clarified at present.It is mainly related to multiple factors such as genetics,metabolism,intestinal flora and immune response.In order to explore the medication rules and mechanism of action of traditional Chinese medicine(TCM)in the treatment of NAFLD,and to provide references for the treatment of NAFLD with TCM and the research and development of new drugs,this article summarizes the TCM pathogenesis of NAFLD(such as"phlegm and blood stasis interlacing","liver depression and spleen deficiency",etc.)and modern etiology and pathogenesis(such as insulin resistance,lipid disorder,mitochondrial dysfunction,oxidative stress,etc.).The clinical research and experimental data at home and abroad in recent years were integrated to analyze the pathological process of NAFLD intervention by TCM through multiple targets,including improving insulin resistance and lipid metabolism disorders,inhibiting oxidative stress and mitochondrial dysfunction,etc.TCM has shown unique advantages in the prevention and treatment of NAFLD.However,the depth of its mechanism analysis and the level of clinical research still need to be improved.In the future,it is necessary to deepen the mechanism research by combining multi-omics technology to accelerate the modernization development of TCM.