Current Analytical Chemistry - Online First

Transition metal oxides are highly effective for dye removal due to their adaptable surface chemistry, availability, and robust mechanical and thermal properties. Among them, Bi4V2O11 nanosheets offer potential due to their morphology and high surface area. To synthesize Bi4V2O11 nanosheets and evaluate their performance in removing malachite green, focusing on the impact of adsorbent amount, contact time, and interfering ions on dye removal efficiency. This study aims to evaluate the performance of Bi4V2O11 nanosheets in removing malachite green dye from aqueous solutions and to examine the effects of adsorbent dosage, contact time, and the presence of coexisting ions on the sorption process.

Bi4V2O11 nanosheets were synthesized and used to remove the malachite green dye. Batch experiments were conducted to study the effects of adsorbent dose, contact time, and coexisting ions (Na⁺, Ca²⁺, and tannic acid). Equilibrium data were fitted to the Langmuir isotherm model to determine the maximum sorption capacity.

Malachite green sorption using Bi4V2O11 nanosheets reached equilibrium within 240 minutes, demonstrating efficient dye removal under the tested conditions. The sorption process conformed to the Langmuir isotherm model, indicating monolayer adsorption with a maximum capacity of 47.27 mg/g. While the presence of Na⁺ and tannic acid had negligible effects on dye removal efficiency, the coexistence of Ca²⁺ significantly reduced the removal efficiency from 95% to 58%, highlighting the potential impact of divalent ions on the adsorption process.

Bi4V2O11 nanosheets are effective adsorbents for malachite green removal, demonstrating high sorption capacity and resilience to Na⁺ and tannic acid interference. However, the presence of Ca²⁺ significantly reduces removal efficiency, highlighting the need for further optimization in practical applications.

Bi4V2O11 nanosheets offer high sorption capacity and structural stability, environment friendly synthesis procedure, making them feasible for small-scale or pre-treatment applications.

Air pollution is a pressing global health and environmental issue, particularly in urban areas where both natural and human-induced factors contribute to deteriorating air quality. While extensive data exists for large industrial cities, less is known about pollution dynamics in smaller, mountainous urban centers. Dushanbe, the capital of Tajikistan, represents a unique setting where seasonal weather patterns and limited industrial activity intersect. This study aims to analyze the air quality in Dushanbe, Tajikistan, by examining the presence of various pollutants over a five-year period (2017-2021).

A longitudinal observational study was conducted using automated air sampling systems at a central monitoring site. Chemical composition of aerosol for metals as well as carbon, sulfur dioxide (SO2), Nitrogen monoxide (NO), Nitrogen dioxide (NO2) and carbon monoxide – (CO) in the atmospheric air of the city of Dushanbe in the period from 2017 to 2021 was analyzed. Atmospheric aerosol samples (C µg/m3, C max, C min) for all metals were determined. Constant monitoring of gas content in the surface layer of the atmosphere was carried out on the territory of the Agency for Hydrometeorology of the Republic of Tajikistan. Descriptive statistics were used to analyze seasonal and annual trends in pollutant levels.

Metals such as Titanium (Ti), Vanadium (V), Chromium (Cr), Manganese (Mg), Iron (Fe), Cobalt (Co), Nickel (Ni) and Copper (Cu) were also detected, which we found in plant organs. These results are in favor of the weather pollution caused by titanium and iron. Average monthly levels of CO, SO2, and NO2 in the atmospheric air of the city of Dushanbe in the period from 2017 to 2021 showed that the variation of air pollution varied according to the seasons and months for each year.

Air quality in Dushanbe is influenced more by geographic and seasonal factors rather than heavy industrial activity. Temporary exceedances in CO and NO2 levels reflect localized emissions from traffic and heating. The absence of toxic heavy metals indicates a relatively low long-term health risk from industrial pollution.

This study provides a comprehensive analysis of Dushanbe’s air quality, demonstrating generally good conditions with short-lived pollution events. Targeted seasonal interventions—such as improved traffic and heating emission controls—are recommended to mitigate transient exposure risks.

Polycyclic aromatic hydrocarbons (PAHs), polychlorinated biphenyls (PCBs), and polychlorinated dibenzo-p-dioxins and furans (PCDD/Fs) are persistent organic pollutants (POPs) with known toxicity and bioaccumulation potential. Smoked meat, a widely consumed food, has been identified as a major dietary source of these contaminants as they are generated due to the incomplete combustion of fuels used in the smoking process. This review examines existing studies on the occurrence of PAHs, PCBs, and PCDD/Fs in smoked meat, with particular attention to the influence of smoking conditions. Factors such as smoking methods, temperature, fuel type, and co-combustion materials, including plastics and chlorine-containing compounds, are analyzed for their role in the formation and accumulation of these pollutants.

A literature search across databases including PubMed, Scopus, ScienceDirect, and Google Scholar for studies published (2010 – 2024) identified relevant studies based on predefined inclusion criteria emphasizing POP levels, formation mechanisms, and analytical methods in smoked meat and related products. Key data were synthesized thematically to identify research trends and gaps.

PAHs have been the most extensively studied in smoked meat, whereas research on PCBs and PCDD/Fs remains limited despite their toxicological significance. The smoking process, particularly the type of fuel and additional materials used, plays a crucial role in the generation of these contaminants. Enhanced analytical techniques have improved detection capabilities, supporting more accurate risk assessments.

Traditional smoking methods are linked to higher POP contamination, especially with chlorine-rich or plastic-containing fuels. Despite advances in analytical techniques, gaps remain in standardizing methods and understanding halogenated POP formation, underscoring the need for harmonized protocols and targeted research on PCBs and PCDD/Fs under practical conditions.

Significant knowledge gaps remain, emphasizing the need for further research to refine smoking practices and enhance food safety standards while preserving the cultural and culinary value of smoked foods.

The chemical composition of Ophiopogonis Radix originating from different districts is somewhat different due to the different planting environment. This difference affects the pharmaceutical efficacy of Ophiopogonis Radix, and therefore poses a challenge to the quality assessment and control of Ophiopogonis Radix. This study aims to develop a method to discriminate Ophiopogonis Radix from various planting districts by using infrared (IR) spectroscopy in combination with a one-dimensional convolutional neural network.

The spectral data of Ophiopogonis Radix samples from five planting districts were collected and preprocessed with Savizkg-Golag (SG) smoothing and the Standard Normal Variate (SNV) algorithm. Back propagation (BP) artificial neural network (ANN) and one-dimensional convolutional neural network (1D-CNN) were employed to build the pattern recognition model for discriminating the investigated Ophiopogonis Radix samples.

The discriminant accuracy of the ANN model after SG and SNV preprocessing reached 94.42% and 96.98% respectively. The discrimination accuracy of the 1D-CNN model after SG and SNV preprocessing reached 98.67% and 99.33%, respectively. It is demonstrated that both the ANN model and the 1D-CNN model are able to discriminate Ophiopogonis Radix samples from different planting districts. Moreover, the developed 1D-CNN model shows higher discrimination accuracy than the ANN model, and SNV preprocessing is better than SG preprocessing for improving the accuracy of the discrimination model.

In this study, the classification performance differences between the SNV-ANN and SNV-CNN models were further compared and analyzed through confusion matrices. The SNV-CNN model exhibited superior classification performance compared to the SNV-ANN model.

IR coupled with 1D-CNN is a practicable and promising approach to discriminate Ophiopogonis Radix from different planting districts. Besides Ophiopogonis Radix, this approach could be used for the planting districts discrimination of other kinds of Traditional Chinese Medicines (TCM). As a high-throughput and data-driven spectroscopic analysis approach, it can be applied to the standardized quality assessment of TCM.

Diabetes clinical guidelines have begun to emphasize the management of cognitive dysfunction in diabetes. Moreover, several studies have shown that long non-coding RNAs (lncRNAs) play critical roles in human diseases. However, no studies have elucidated whether lncRNAs are involved in the pathogenesis of diabetes-associated cognitive dysfunction (DACD).

The hippocampi of male mice with homozygous leptin receptor-deficient T2DM and their littermates were analyzed via high-throughput sequencing. RNA and protein sequencing data were utilized to identify differentially expressed (DE) mRNAs, lncRNAs, and proteins between diabetes mellitus and control groups. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were performed for DE-mRNAs-DE-proteins. Subsequently, lncRNA-mRNA-pathway and lncRNA-miRNA-mRNA networks were constructed. Quantitative real-time PCR (qRT-PCR) was conducted to verify the expression trends of key lncRNAs in DACD.

We identified upregulated and downregulated mRNAs, lncRNAs, and proteins in the diabetes group. Eleven DE-mRNAs-DE-proteins were associated with inflammatory response, lipid/steroid metabolism, and cell growth. The lncRNA-mRNA-pathway network contained 36 lncRNA-mRNA pairs linked to 8 KEGG pathways. Twenty-five lncRNAs corresponding to Apoa1 were identified as key candidates. Subcellular localization and ceRNA network analyses suggested that lncRNA 3110039I08Rik and lncRNA Gm36445 may regulate DACD. qRT-PCR confirmed their increased expression in diabetic mice.

Our findings reveal that lncRNA 3110039108Rik and Gm36445 may act as critical regulators in DACD pathogenesis through competing endogenous RNA (ceRNA) networks. These lncRNAs represent potential biomarkers for early diagnosis and therapeutic targets, offering new insights into the management of cognitive dysfunction in diabetes.

Our results identified two novel lncRNAs that may play critical roles in DACD.

In Traditional Chinese Medicine (TCM), BSS refers to impaired circulation or stagnation of blood flow and formation of bruises. The primary therapeutic strategy to treat BSS involves invigorating blood circulation. PRR is a widely used TCM herb for treating acute and critical diseases caused by BSS. However, the anticoagulant effects of different compounds of PRR on BSS remain elusive. The aim of the study was to investigate the pharmacological role of different chemical constituents of Paeoniae Radix Rubra (PRR) in the modulation of anticoagulation in Blood Stasis Syndrome (BSS). This study aimed to analyze the therapeutic effect of PRR on BSS and to assess the ameliorative effect of different chemical constituents of PRR on blood circulation, clotting time, and platelet aggregation in rats with acute BSS.

Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP) was used to screen the targets of PRR, and genes causing BSS were predicted using PharmGKB, OMIM, and TTD databases. Intersected genes between PRR and BSS targets were visualized in Venn diagrams. Core target networks of Protein-Protein Interaction (PPI) and cross-targets were constructed using Cytoscape 3.7.1, and the cross-targets were enriched using the Database for Annotation, Visualization, and Integrated Discovery (DAVID) database. Furthermore, the effects of PRR on platelet aggregation, plasma viscosity, and whole blood viscosity in the rats with BSS were examined by blood rheology and other methods. The serum levels of Endothelin-1 (ET-1), Nitric Oxide (NO), Thromboxaneb2 (TXB2), and 6-keto-Prostaglandin F1 α (6-keto-PGF1α) in the rats were measured by the Enzyme-Linked Immunosorbent Assay (ELISA) method.

The main active compounds of PRR, including total glycosides, flavonoids, and polysaccharides, were identified using the TCMSP database. A total of 31 cross-targets were obtained from the intersection between 129 active targets of PRR and 345 causative genes of BSS. PPI network identified genes such as Albumin (ALB), SRC Proto-Oncogene, Non-Receptor Tyrosine Kinase (SRC), and AKT Serine/Threonine Kinase 1 (AKT1) as the core targets of PRR in alleviating BSS. Enrichment analysis showed that the common targets were mainly associated with several biological processes, including lipid and atherosclerosis, adherens junction, and focal adhesion. Following the intervention with PRR extract, the whole blood viscosity and plasma viscosity were reduced, and platelet aggregation was inhibited in the model rats in comparison to the model group. Moreover, PRR treatment also promoted thrombin time (TT), prothrombin time (PT), and Activated Partial Thromboplastin Time (APTT), increased the level of NO and 6-keto-PGF1α, but reduced the level of Fibrinogen content (FIB) and ET-1 and TXB2 in the serum of the model rats.

The present research systematically explored the anticoagulant effect of the chemical constituents of PRR on BSS in rats, applying network pharmacology analysis.

The current findings provided a theoretical foundation for the pharmacological basis of using PRR in the management of BSS.

Inflammatory disorders profoundly affect quality of life, with existing treatments often limited by resistance, adverse effects, and administration challenges. Andrographis paniculata, highly esteemed for its potent anti-inflammatory efficacy, harbors andrographolide, a pharmacologically active compound whose clinical utilization is impeded by its limited aqueous solubility and reduced oral bioavailability.

To address these limitations, we synthesized a mixture of andrographolide sulfonated derivatives to improve solubility. The major derivatives were isolated and analyzed qualitatively by NMR and UHPLC-Q/TOF-MS. Their anti-inflammatory effects were evaluated using a zebrafish inflammation model, and the most active derivatives were further analyzed through network pharmacological analysis to uncover the underlying anti-inflammatory mechanisms.

The synthesis of andrographolide sulfonate derivatives enhanced andrographolide’s solubility. Structural characterization of the seven predominant derivatives was performed. Testing in a zebrafish model revealed that andrographolide and three sulfonated derivatives substantially reduced inflammation. Network pharmacology analysis identified significant connections in the “active compounds-inflammation targets-pathways-therapeutic effects” network, highlighting important biological processes and six key molecular targets (PRKCA, PRKCB, MAPK14, IL6, CASP3, and CDK4) associated with the anti-inflammatory actions of these derivatives.

This integrative chemical–bioinformatic workflow significantly enhances the solubility of andrographolide while preserving its anti-inflammatory potency and identifying six key inflammatory targets. It therefore provides a transferable blueprint for optimising hydrophobic natural products and accelerating anti-inflammatory drug discovery.

Overall, this study not only improves the solubility and maintains the anti-inflammatory efficacy of andrographolide through sulfonation but also elucidates the underlying potential mechanisms of action of its sulfonated derivative mixture.

Geographical location plays a critical role in the distribution and potency of medicinal plants. Climate, soil composition, and other factors significantly affect the chemical composition of plants and their medicinal properties. This study aims to investigate how the expression of biodiversity manifests in the phytocompound of Hydrocotyle rotundifolia from different biogeographical locations across the Indian subcontinent.

The study analyzed the amount of genistein in the aerial part of H. rotundifolia across three different biogeographical zones using a precise, simple, and highly reproducible validated HPTLC method and adopted different standard spectroscopic methods for soil characterization.

The quantity of genistein was found to be highest (0.74%) in the plants growing in the soil of the northeast region, where the available nitrogen (23.45 Kgha^-1) and potassium (267.354 Kgha^-1) were also highest among the three regions.

Correlating the soil characters and climatic factors, it may be concluded that the Northeast region, with its favorable soil conditions and climatic support, is the ideal location for growing this plant and producing genistein.

This information is invaluable for applications in agriculture, pharmaceuticals, and environmental studies because understanding the distribution and concentration of phytocompounds across different locations can have numerous applications in these fields.

Gum tragacanth is used as a substance to increase viscosity, stabilize, emulsify, and suspend other substances. In recent years, it has emerged as a promising therapeutic agent for tissue engineering, regenerative medicine, cosmetics, and food adjuvants. Therefore, characterizing its temperature-dependent viscosity is crucial for its pilot-scale applications. Therefore, the main objective of the present work is the characterization of the temperature dependent coefficient of viscosity and surface tension of gum tragacanth to establish it as an alternative source of natural gums for commercial applications.

The effect of temperature on the rheological behaviours of the polymeric solution was studied. Furthermore, the Arrhenius, Gibbs–Helmholtz, Frenkel–Eyring, and Eotvos equations were utilized to compute the temperature coefficient, viscosity, surface tension, activation energy, Gibbs free energy, Reynolds number, and entropy of fusion, respectively.

It was determined that the activation energy of gum tragacanth was 1559.70 kJ/mol. Changes in entropy and enthalpy were found to be 56.34 and 1122.80 kJ/mol, respectively. The Reynold number's computed value was 0.0053.

Discussion: As the temperature increased, there was a noticeable decrease in both surface tension as well as apparent viscosity. In contrast to Albizia lebbac gum, the current study found that solutions made from Gum Tragacanth seed polymers had a smaller impact by changes in temperature.

Gum tragacanth polymer's exceptional physicochemical qualities make it a promising excipient for drug formulation in the years to come, paving the way for its widespread use in food, cosmetics, and pharmaceutical industries.

To investigate the pharmacodynamic material basis and potential mechanism of Aster tataricus L. total flavonoids (ATF) in treating isoniazid (INH) and rifampicin (RIF)-induced drug-induced liver injury (DILI) in C57BL/6 mice

ATF was extracted using ultrasonic extraction and purified with AB-8 macroporous adsorbent resin. A DILI model was established in male C57BL/6 mice using INH and RIF. Histopathological changes were assessed by HE staining, and serum levels of ALT and AST, as well as liver levels of SOD, MDA, GSH-Px, and T-AOC, were measured. UPLC-Q-Exactive-MS was used to analyze ATF and serum components in DILI mice, followed by network pharmacology analysis and molecular docking validation.

TThe extraction rate of ATF was 31.9%, and the purification rate was 83.1%. ATF treatment alleviated cell necrosis and inflammation, reduced organ index, and normalized biochemical indices, with the best effects observed at low doses. UPLC-Q-Exactive-MS identified 15 blood-entry components, 9 prototype components, and 4 core targets with high binding energies.

Efficient extraction and purification methods for total flavonoids from Aster tataricus L. were developed. Their pharmacological basis and potential targets for treating DILI were identified, providing a theoretical basis for DILI treatment.

This study provides a theoretical basis for the treatment of DILI using ATF. The developed extraction and purification methods efficiently obtained ATF, and its pharmacological basis and potential targets were identified. This research offers a new direction for exploring natural products from Traditional Chinese Medicine for DILI treatment.