Objective To investigate changes in the distribution of Oncomelania hupensis snails in Yixing City, Jiangsu Province, from 2008 to 2024, and to provide insights to guide formulation of O. hupensis snail investigation and surveillance programs. Methods Data from O. hupensis snail surveys in Yixing City from 2008 to 2024 were collected. Trends in snail habitat site numbers, snail-infested areas, proportion of total area with snail habitats, occurrence of frames with living snails, and density of living snails in snail habitats in hilly regions of Yixing City were evaluated from 2008 to 2024 by applying a Joinpoint regression model to collect annual percent change (APC) and average annual percent change (AAPC) data. Results From 2008 to 2024, a total of 193.815 hm2 of snail-infested area was found within Yixing City, of which 191.765 hm2 (accounting for 98.94%) was distributed in hilly regions. A total of 344 snail infestation sites in hilly regions were identified. The average occurrence rate of living snail frames in snail habitats was 8.650% and the average living snail density in snail habitats was 0.246 per 0.1 m2. No Oncomelania snails were positively identified. The number of snail habitat sites in hilly regions of Yixing City showed no significant decreasing trend (AAPC=-2.8%, P=0.527). Similarly, no significant increasing trend in snail-infested area (APC=AAPC=5.7%, P=0.328) was found. The occurrence rate of living snail frames in snail habitats showed no significant increasing trend (APC=AAPC=5.1%, P=0.583). Living snail density in snail habitats also showed no significant increasing trend (APC=AAPC=3.2%, P=0.598). Conclusions From 2008 to 2024, snail infestation has persisted in the hilly areas of Yixing City with an unclear variation trend. The quality of snail investigation and snail surveillance system should be strengthened to permit timely identification of hidden dangers and rapid risk responses, thereby preventing schistosomiasis outbreaks.

Objective: To evaluate the feasibility of dynamic contrast-enhanced MRI (DCE-MRI) in differentiating tumor deposits (TDs) from metastatic lymph nodes (MLNs) in rectal cancer. Materials and Methods: A retrospective analysis was conducted on 70 patients with rectal cancer, including 168 lesions (70 TDs and 98 MLNs confirmed by histopathology), who underwent pretreatment MRI and subsequent surgery between March 2019 and December 2022. The morphological characteristics of TDs and MLNs, along with quantitative parameters derived from DCE-MRI (K trans , kep, and v e) and DWI (ADCmin, ADCmax, and ADCmean), were analyzed and compared between the two groups.Multivariable binary logistic regression and receiver operating characteristic (ROC) curve analyses were performed to assess the diagnostic performance of significant individual quantitative parameters and combined parameters in distinguishing TDs from MLNs. Results: All morphological features, including size, shape, border, and signal intensity, as well as all DCE-MRI parameters showed significant differences between TDs and MLNs (all P < 0.05). However, ADC values did not demonstrate significant differences (all P > 0.05). Among the single quantitative parameters, v e had the highest diagnostic accuracy, with an area under the ROC curve (AUC) of 0.772 for distinguishing TDs from MLNs. A multivariable logistic regression model incorporating short axis, border, v e, and ADC mean improved diagnostic performance, achieving an AUC of 0.833 (P = 0.027). Conclusion The combination of morphological features, DCE-MRI parameters, and ADC values can effectively aid in the preoperative differentiation of TDs from MLNs in rectal cancer.

Objective: To evaluate the feasibility of dynamic contrast-enhanced MRI (DCE-MRI) in differentiating tumor deposits (TDs) from metastatic lymph nodes (MLNs) in rectal cancer. Materials and Methods: A retrospective analysis was conducted on 70 patients with rectal cancer, including 168 lesions (70 TDs and 98 MLNs confirmed by histopathology), who underwent pretreatment MRI and subsequent surgery between March 2019 and December 2022. The morphological characteristics of TDs and MLNs, along with quantitative parameters derived from DCE-MRI (K trans , kep, and v e) and DWI (ADCmin, ADCmax, and ADCmean), were analyzed and compared between the two groups.Multivariable binary logistic regression and receiver operating characteristic (ROC) curve analyses were performed to assess the diagnostic performance of significant individual quantitative parameters and combined parameters in distinguishing TDs from MLNs. Results: All morphological features, including size, shape, border, and signal intensity, as well as all DCE-MRI parameters showed significant differences between TDs and MLNs (all P < 0.05). However, ADC values did not demonstrate significant differences (all P > 0.05). Among the single quantitative parameters, v e had the highest diagnostic accuracy, with an area under the ROC curve (AUC) of 0.772 for distinguishing TDs from MLNs. A multivariable logistic regression model incorporating short axis, border, v e, and ADC mean improved diagnostic performance, achieving an AUC of 0.833 (P = 0.027). Conclusion The combination of morphological features, DCE-MRI parameters, and ADC values can effectively aid in the preoperative differentiation of TDs from MLNs in rectal cancer.

Objective: To evaluate the feasibility of dynamic contrast-enhanced MRI (DCE-MRI) in differentiating tumor deposits (TDs) from metastatic lymph nodes (MLNs) in rectal cancer. Materials and Methods: A retrospective analysis was conducted on 70 patients with rectal cancer, including 168 lesions (70 TDs and 98 MLNs confirmed by histopathology), who underwent pretreatment MRI and subsequent surgery between March 2019 and December 2022. The morphological characteristics of TDs and MLNs, along with quantitative parameters derived from DCE-MRI (K trans , kep, and v e) and DWI (ADCmin, ADCmax, and ADCmean), were analyzed and compared between the two groups.Multivariable binary logistic regression and receiver operating characteristic (ROC) curve analyses were performed to assess the diagnostic performance of significant individual quantitative parameters and combined parameters in distinguishing TDs from MLNs. Results: All morphological features, including size, shape, border, and signal intensity, as well as all DCE-MRI parameters showed significant differences between TDs and MLNs (all P < 0.05). However, ADC values did not demonstrate significant differences (all P > 0.05). Among the single quantitative parameters, v e had the highest diagnostic accuracy, with an area under the ROC curve (AUC) of 0.772 for distinguishing TDs from MLNs. A multivariable logistic regression model incorporating short axis, border, v e, and ADC mean improved diagnostic performance, achieving an AUC of 0.833 (P = 0.027). Conclusion The combination of morphological features, DCE-MRI parameters, and ADC values can effectively aid in the preoperative differentiation of TDs from MLNs in rectal cancer.

Under the background of carbon peaking and carbon neutrality goals, the Ministry of Ecology and Environment, together with 15 national ministries and commissions, has formulated the Implementation Plan on Establishing a Carbon Footprint Management System, and it is urgent for traditional Chinese medicine(TCM) pharmaceutical enterprises to carry out research on carbon footprint accounting methods of related products. Based on the life cycle assessment(LCA) theory, taking mulberry leaf extract produced by a certain enterprise as an example, this study analyzed the carbon footprint of TCM extracts during the life cycle. The results show that for every 1 kg of product produced, the carbon emissions from the stages of raw material acquisition, transportation, and extract production are-20.569, 1.205, and 173.577 kgCO_2eq(CO_2 equivalent), respectively. The carbon footprint of the product is 154.213 kgCO_2eq·kg~(-1). In addition, the carbon emission is the highest in the production stage, in which the consumption of ethanol solvents makes the greatest contribution to the carbon footprint, accounting for 25.71%, more than one-fourth of the total carbon footprint. The second contribution was from the treatment process of TCM residues, accounting for 19.67%, closely followed by wastewater treatment(17.71%), the consumption of hot steam(17.43%), and drinking water(16.90%). The consumption of electric power and packaging materials has a smaller carbon emission of 2.58%. In particular, the carbon emission caused by the consumption of packaging materials is only 0.04%, which is negligible. The results of the study are expected to provide a reference for TCM enterprises to carry out research on the carbon footprint of products, offer ideas for collaborative innovation in reducing pollution and carbon emissions throughout the entire industry chain of TCM, and develop new quality productivity of modern TCM industry based on green and low-carbon manufacturing.
Morus/chemistry* ; Plant Leaves/chemistry* ; Carbon Footprint ; Drugs, Chinese Herbal/chemistry* ; Plant Extracts/analysis* ; Medicine, Chinese Traditional

Macroporous resin adsorption column chromatography, silica gel column chromatography, ODS column chromatography, and semi-preparative high-performance liquid chromatography, combined with analytical methods such as NMR and MS, were employed to separate and identify compounds from the 70% ethanol extract of Ajania purpurea. A total of 30 compounds were isolated and identified, including 13 phenolic acids, 7 coumarins, 2 lignans, 1 flavonoid, 2 sesquiterpenes, 1 steroid, and 4 others. Among them, compounds 1 and 2 were newly discovered compounds, and compounds 4, 6, 8, 12, 14-23, 25, 28, and 30 were isolated from Ajania plants for the first time. Bioactivity screening showed that multiple compounds significantly inhibited the production of nitric oxide in lipopolysaccharide-stimulated RAW264.7 cells in a dose-dependent manner. Furthermore, compound 2 elevated the levels of glutathione in LPS-induced BEAS-2B cells, reduced the expression of pro-inflammatory cytokines such as tumor necrosis factor(TNF)-α, interleukin(IL)-6, and IL-1β, enhanced the mRNA of GPX4, HMOX1, NFE2L2, and enhanced protein levels of GPX4, HO-1, Nrf2, and SLC7A11, demonstrating potential anti-ferroptotic effect.
Mice ; Animals ; Lignans/isolation & purification* ; RAW 264.7 Cells ; Humans ; Nitric Oxide ; Tumor Necrosis Factor-alpha/immunology* ; Drugs, Chinese Herbal/isolation & purification* ; NF-E2-Related Factor 2/metabolism* ; Macrophages/metabolism* ; Interleukin-6/immunology*

With the widespread use of antibiotics, drug-resistant bacterial infections have become a significant threat to human health. Finding new antibacterial strategies that can effectively control drug-resistant bacterial infections has become an urgent task. Unlike small molecule drugs that target bacterial proteins, antisense oligonucleotide (ASO) can target genes related to bacterial resistance, pathogenesis, growth, reproduction and biofilm formation. By regulating the expression of these genes, ASO can inhibit or kill bacteria, providing a novel approach for the development of antibacterial drugs. To overcome the challenge of delivering antisense oligonucleotide into bacterial cells, various drug delivery systems have been applied in this field, including cell-penetrating peptides, lipid nanoparticles and inorganic nanoparticles, which have injected new momentum into the development of antisense oligonucleotide in the antibacterial realm. This review summarizes the current development of small nucleic acid drugs, the antibacterial mechanisms, targets, sequences and delivery vectors of antisense oligonucleotide, providing a reference for the research and development of antisense oligonucleotide in the treatment of bacterial infections.

Objective: To evaluate the feasibility of dynamic contrast-enhanced MRI (DCE-MRI) in differentiating tumor deposits (TDs) from metastatic lymph nodes (MLNs) in rectal cancer. Materials and Methods: A retrospective analysis was conducted on 70 patients with rectal cancer, including 168 lesions (70 TDs and 98 MLNs confirmed by histopathology), who underwent pretreatment MRI and subsequent surgery between March 2019 and December 2022. The morphological characteristics of TDs and MLNs, along with quantitative parameters derived from DCE-MRI (K trans , kep, and v e) and DWI (ADCmin, ADCmax, and ADCmean), were analyzed and compared between the two groups.Multivariable binary logistic regression and receiver operating characteristic (ROC) curve analyses were performed to assess the diagnostic performance of significant individual quantitative parameters and combined parameters in distinguishing TDs from MLNs. Results: All morphological features, including size, shape, border, and signal intensity, as well as all DCE-MRI parameters showed significant differences between TDs and MLNs (all P < 0.05). However, ADC values did not demonstrate significant differences (all P > 0.05). Among the single quantitative parameters, v e had the highest diagnostic accuracy, with an area under the ROC curve (AUC) of 0.772 for distinguishing TDs from MLNs. A multivariable logistic regression model incorporating short axis, border, v e, and ADC mean improved diagnostic performance, achieving an AUC of 0.833 (P = 0.027). Conclusion The combination of morphological features, DCE-MRI parameters, and ADC values can effectively aid in the preoperative differentiation of TDs from MLNs in rectal cancer.

On the basis of that the fluorescence wavelength of copper nanoclusters(CuNCs)could cover the entire visible region,multicolor fluorescent CuNCs/starch composites were prepared and applied in fingermark development.With L-glutathione as the reducing agent and protective ligand,blue emissive and orange emissive CuNCs solutions were obtained in alkaline solutions at 90℃and 25℃,respectively.With the aggregation-induced emission effect induced by ethanol as a poor solvent,the fluorescence of orange emissive CuNCs with a higher intensity was achieved in an ethanol-water solution.With ascorbic acid as the reducing agent and 3-mercaptopropionic acid as the protective agent,green emissive CuNCs solution was prepared in an acid solution.Particle morphologies,chemical compositions and optical properties of these three CuNCs above were investigated using physical characterization and spectroscopic analysis,indicating that well-dispersed CuNCs had excellent photoluminescent properties.These CuNCs solutions were combined with starch to form composite powders by simply drying.The influences of the type of CuNCs and the ratio of CuNCs to starch on the emission wavelength and fluorescence intensity of the products were studied.The obtained CuNCs/starch composites could emit blue,green and orange fluorescence under 365 nm ultraviolet light,respectively,which were suitable for fingermark development.Minutiae and partial level-3 features of latent fingermarks could be effectively developed.High-quality fluorescence fingermark images would be captured using appropriate optical filters to eliminate background interference of various substrates.

As a cheap and effective antibiotic,sulfonamides are often used in animal husbandry.However,their residues in animal-derived foodstuffs will threaten human health.Consequently,a high-performance liquid chromatography(HPLC)method integrated with supramolecular solvent microextraction was successfully established for simultaneous quantification of sulfonamide residues sulfachlorpyridazine,sulfamethoxazole,sulfamethoxypyridazine and sulfadimethoxine in milk matrices.This approach exhibited prominent characteristics of operational simplicity,environmental sustainability,and high extraction efficiency.The supramolecular solvents prepared by tributyl octylphosphine tetrafluoroborate and tetrahydrofuran were employed as extraction solvents.The analytes underwent isolation and concentration via dispersive liquid-liquid microextraction(DLLME)prior to quantitative determination using high-performance liquid chromatography(HPLC).The composition and microscopic morphology of the supramolecular solvent were characterized through a series of analytical techniques,including phase diagram,Fourier transform infrared spectroscopy,scanning electron microscopy,and inverted fluorescence microscopy and so on.The density and pH value of supramolecular solvents were determined.The extraction conditions were optimized through the one-factor experiments.The experimental results demonstrated that under the optimal extraction conditions,the four kinds of sulfonamide antibiotics exhibited excellent linearity within respective detection range(R2 ≥ 0.9998)and the limits of detection(LOD)were 0.67-1.45 μg/L.Compared with literature methods,this approach offered some advantages such as simplicity of operation and less reagent consumption,and could be used for analysis and detection of sulfonamide antibiotic residues in milk samples.The present method provided technical support for food safety regulation and paved a new way for the application of supramolecular solvents in the field of extraction and separation.