This paper introduces a real-world cohort research model for community-acquired pneumonia （CAP） based on the Jiangsu Traditional Chinese Medicine （TCM） Dominant Diseases Diagnosis and Treatment Data Platform. Firstly， data cleaning is performed by standardizing diagnosis， symptoms， treatment and imaging， intelligently extracting unstructured information， and cleaning and constructing a standardized database. Secondly， for cohort establishment， CAP patients across the province are screened in accordance with CAP diagnostic criteria to build a high-quality disease-specific cohort. Lastly， in terms of protocol design， the characteristics of TCM research and the CAP disease profile are considered to determine appropriate inclusion and exclusion criteria， estimate sample size， define interventions， outcomes and economic evaluations， providing a reference for real-world TCM research on CAP.

This paper introduces a real-world cohort research model for community-acquired pneumonia （CAP） based on the Jiangsu Traditional Chinese Medicine （TCM） Dominant Diseases Diagnosis and Treatment Data Platform. Firstly， data cleaning is performed by standardizing diagnosis， symptoms， treatment and imaging， intelligently extracting unstructured information， and cleaning and constructing a standardized database. Secondly， for cohort establishment， CAP patients across the province are screened in accordance with CAP diagnostic criteria to build a high-quality disease-specific cohort. Lastly， in terms of protocol design， the characteristics of TCM research and the CAP disease profile are considered to determine appropriate inclusion and exclusion criteria， estimate sample size， define interventions， outcomes and economic evaluations， providing a reference for real-world TCM research on CAP.

ObjectiveThe present study aimed to investigate alterations in white matter microstructure and spontaneous neural activity in male college smokers, and to further explore their associations with nicotine dependence. Given that adolescence and early adulthood represent critical periods for brain maturation, particularly for white matter development, understanding the neural correlates of smoking behavior during this stage is of substantial importance for both neuroscience and public health. MethodsA total of 115 male undergraduate students were initially recruited for this study. After quality control and exclusion procedures, 52 male college smokers and 42 demographically matched healthy non-smokers were included in the final analysis. All participants underwent multimodal magnetic resonance imaging (MRI), including diffusion tensor imaging (DTI) and resting-state functional MRI (rs-fMRI). White matter fiber tracts were reconstructed using the automated fiber quantification (AFQ) method, which enables precise identification and quantification of major fiber bundles. Eighteen major white matter tracts were segmented for each participant. Along the core trajectory of each tract, 100 equidistant nodes were sampled. Fractional anisotropy (FA) was calculated at each node to assess white matter microstructural integrity, while amplitude of low-frequency fluctuation (ALFF) was computed to evaluate spontaneous neural activity within white matter tracts. Between-group differences in FA and ALFF were assessed using two-sample t-tests, with appropriate corrections applied for multiple comparisons. Furthermore, Pearson correlation analyses were conducted to examine the relationships between imaging-derived metrics (FA and ALFF values in regions showing significant group differences) and nicotine dependence severity, as measured by the Fagerström test for nicotine dependence (FTND). ResultsCompared with healthy non-smokers, male college smokers exhibited significantly increased FA values in several white matter tracts, including the left thalamic radiation, right corticospinal tract, forceps major of the corpus callosum, left uncinate fasciculus, and right arcuate fasciculus. These findings suggest altered microstructural organization or increased directional coherence within these pathways. In addition, smokers demonstrated significantly elevated ALFF values in the forceps major, right uncinate fasciculus, and left arcuate fasciculus, indicating enhanced spontaneous neural activity in these white matter regions. Correlation analyses revealed that FA values in the left thalamic radiation and right corticospinal tract were negatively correlated with FTND scores, suggesting that higher levels of nicotine dependence were associated with reduced microstructural integrity or altered fiber organization in these regions. In contrast, ALFF values in the forceps major and right uncinate fasciculus were positively correlated with FTND scores, indicating that greater nicotine dependence was associated with increased spontaneous neural activity in specific white matter pathways. ConclusionThe present study provides evidence that male college smokers exhibit distinct alterations in both white matter microstructure and functional activity. These abnormalities are not uniformly distributed but rather localized to specific fiber tracts implicated in sensorimotor processing, interhemispheric communication, and higher-order cognitive and emotional regulation. Importantly, the observed associations between imaging metrics and nicotine dependence severity suggest that these structural and functional alterations may reflect neurobiological mechanisms underlying addiction. The combination of AFQ-based tract profiling and multimodal MRI offers a sensitive approach for detecting subtle changes along white matter pathways, highlighting its potential utility in identifying neuroimaging biomarkers of nicotine dependence. Overall, these findings indicate that smoking during early adulthood may disrupt ongoing white matter maturation, potentially leading to long-term consequences for brain function. This study provides novel insights into the neural basis of nicotine dependence and underscores the importance of early intervention and prevention strategies targeting young smokers.

Objective To gain insights into the biological characteristics of different populations of Culex tritaeniorhynchus within and around the Yellow Sea wetland from the perspective of the occurrence of resistance, we investigated the levels of resistance to deltamethrin and kdr gene mutation in the wetland and its peripheral areas. Methods Specimens were collected from Cx. tritaeniorhynchus populations at two monitoring sites in the Rare Bird National Nature Reserve and Tiaozi Ni Wetland Scenic Area, and also from two populations in Yancheng City and the Liuhe District of Nanjing, and the resistance of these mosquitoes to deltamethrin was determined using the CDC biotest bottle method. For each concentration of deltamethrin assessed, a random subset of exposed specimens was selected for amplification of the kdr gene fragment, followed by Sanger sequencing to identify and analyze resistance-associated mutations. Results The LC50 levels of deltamethrin among mosquitoes from the four populations in Luhe, Yancheng, the Rare Bird National Nature Reserve and the Tiaozi Ni Wetland Scenic Area were 2.048 5, 7.798 2, 3.473 3, and 17.695 5 mg/mL, respectively, with corresponding concentrations of deltamethrin ranging from 0.005 to 5.000,0.050 to 50.000,0.050 to 25.000 and 0.050 to 50.000 mg/mL, respectively. Furthermore, the ranges of the KT50 values were 11.76-107.43, 67.05-216.30,29.77-107.43 and 28.40-329.51 min; the 1-h knockdown rates were 34.58%-99.15%, 9.52%-43.80%, 55.09%-73.01%, and 10.09%-68.07%; and the 24-h mortality rates were 12.15%-67.52%,9.52%-79.56%,13.17%-82.21%, and 11.01%-78.99%, respectively. With respect to kdr gene mutation, we assayed a total of 63,70,59, and 57 mosquitoes for the four populations, for which we detected L1014F mutation frequencies of 14.29%, 35.00%, 20.34%, and 31.58%, respectively, with a majority of these mutations being heterozygous for resistance. In addition, five adult mosquitoes were identified has having synonymous mutations at site 1011[i. e. , AAT(asparagine)mutation to AAC(asparagine)]. Conclusions Our findings revealed the clear resistance of Cx. tritaeniorhynchus to deltamethrin in the Yancheng region of the Yellow Sea wetland, and the resistance phenotype and kdr frequency of Cx. tritaeniorhynchus in the wetland environment were comparable to those of Cx. tritaeniorhynchus in the wetland environment, thereby indicating that the resistance of different populations of Cx. tritaeniorhynchus was homogeneous under the pressure of different insecticide selection within and around the wetland. However, the underlying mechanisms need to be further studied.

Objective This study aimed to investigate the seasonal variation of mosquitoes in Yantai, Shandong Province, and provide a scientific basis for mosquito and mosquito-borne disease control. Methods From March to November for each of the years between 2020 and 2023, adult mosquitoes were collected from different habitats, including parks, hospitals, urban residential areas, rural households and livestock sheds, in 13 counties of Yantai City using a mosquito trap lamp method, among which, female mosquitoes were separated and identified, and the numbers were counted. We used the circular distribution method to analyze the temporal distribution characteristics of mosquito density. Results The γ values obtained for mosquitoes in Yantai from 2020 to 2023, the distribution of mosquitoes in different habitats, and dominant mosquito species in different months showed strong seasonality, with values ranging from 0.7461 to 0.8531(P ＜ 0.05). The peak period of seasonal variation in mosquitoes occurred from June 28thto September 13th, with August 5thbeing identified as the peak day. The peak periods of seasonal variation in mosquitoes in residential areas, parks, hospitals, peasant households, and animals sheds were observed from June 24thto September 14th, June 25thto September 10th, June 22ndto September 12th, July 1stto September 9th, and July 2ndto September 17th, respectively, with corresponding peak days on August 4th,3rd, 2nd, 5th, and 9th, respectively. The peak periods of Culex pipiens pallens, Aedes albopictus, and Anopheles sinensis were from June 26thto September 11th, June 28thto September 17th, and July 12thto September 17th, respectively, with corresponding peak days on August 3rd,7th, and 14th, respectively. Conclusions Our findings in this study revealed that the peak of mosquito activity in Yantai was concentrated in early August, with a peak period extending from June 28thto September 13th, and there were differences between different habitats(with peak periods for rural households and livestock sheds occurring later than those in residential areas, parks, and hospitals). Moreover, with respect to the mosquito species, populations of Cx. pipiens pallens and Ae. albopictus peaked earlier than those of An. sinensis. Based on these findings, we recommend that city-wide mosquito control work should commence in late June, and include appropriate early prevention and control measures for key habitats, such as livestock sheds, and dominant mosquito species, such as Cx. pipiens pallens, to minimize the density of mosquito vectors and the risk of disease transmission.

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.

Alzheimer’s disease (AD) is a central neurodegenerative disease characterized by progressive cognitive decline and memory impairment in clinical. Currently, there are no effective treatments for AD. In recent years, a variety of therapeutic approaches from different perspectives have been explored to treat AD. Although the drug therapies targeted at the clearance of amyloid β-protein (Aβ) had made a breakthrough in clinical trials, there were associated with adverse events. Neuroinflammation plays a crucial role in the onset and progression of AD. Continuous neuroinflammatory was considered to be the third major pathological feature of AD, which could promote the formation of extracellular amyloid plaques and intracellular neurofibrillary tangles. At the same time, these toxic substances could accelerate the development of neuroinflammation, form a vicious cycle, and exacerbate disease progression. Reducing neuroinflammation could break the feedback loop pattern between neuroinflammation, Aβ plaque deposition and Tau tangles, which might be an effective therapeutic strategy for treating AD. Traditional Chinese herbs such as Polygonum multiflorum and Curcuma were utilized in the treatment of AD due to their ability to mitigate neuroinflammation. Non-steroidal anti-inflammatory drugs such as ibuprofen and indomethacin had been shown to reduce the level of inflammasomes in the body, and taking these drugs was associated with a low incidence of AD. Biosynthetic nanomaterials loaded with oxytocin were demonstrated to have the capability to anti-inflammatory and penetrate the blood-brain barrier effectively, and they played an anti-inflammatory role via sustained-releasing oxytocin in the brain. Transplantation of mesenchymal stem cells could reduce neuroinflammation and inhibit the activation of microglia. The secretion of mesenchymal stem cells could not only improve neuroinflammation, but also exert a multi-target comprehensive therapeutic effect, making it potentially more suitable for the treatment of AD. Enhancing the level of TREM2 in microglial cells using gene editing technologies, or application of TREM2 antibodies such as Ab-T1, hT2AB could improve microglial cell function and reduce the level of neuroinflammation, which might be a potential treatment for AD. Probiotic therapy, fecal flora transplantation, antibiotic therapy, and dietary intervention could reshape the composition of the gut microbiota and alleviate neuroinflammation through the gut-brain axis. However, the drugs of sodium oligomannose remain controversial. Both exercise intervention and electromagnetic intervention had the potential to attenuate neuroinflammation, thereby delaying AD process. This article focuses on the role of drug therapy, gene therapy, stem cell therapy, gut microbiota therapy, exercise intervention, and brain stimulation in improving neuroinflammation in recent years, aiming to provide a novel insight for the treatment of AD by intervening neuroinflammation in the future.

Objective To analyze the changes in myocardial injury markers and cardiac function in patients with hypertrophic obstructive cardiomyopathy (HOCM) after Liwen surgery. Methods A retrospective analysis was conducted on the clinical data of HOCM patients who underwent Liwen surgery at the Department of Cardiac Surgery, Wuhan Asia Heart Hospital from December 2019 to April 2023, mainly including preoperative and postoperative dynamic follow-up laboratory test results and echocardiograms. Results A total of 42 patients were included, with 25 males and 17 females, aged (44.76±17.72) years, and a postoperative follow-up time of (15.02±6.97) months. The myocardial troponin level of the patients decreased from preoperative 0.03 (0.02, 0.06) ng/mL to postoperative 0.02 (0.01, 0.05) ng/mL (P=0.006), and the N-terminal pro-brain natriuretic peptide level decreased from preoperative 748.95 (337.40, 1600.75) ng/L to postoperative 367.15 (126.93, 1030.25) ng/L (P<0.001). After surgery, the left atrial diameter of the patients decreased from preoperative (4.18±0.57) cm to postoperative (3.93±0.55) cm (P=0.004), the end-diastolic interventricular septum thickness decreased from preoperative 2.25 (1.90, 2.75) cm to postoperative 1.70 (1.50, 1.90) cm (P<0.001), the left ventricular mass index decreased from preoperative 211.73 (172.28, 261.54) g/m2 to postoperative 156.78 (132.34, 191.36) g/m2 (P<0.001), the left ventricular weight decreased from preoperative 368.89 (292.34, 477.72) g to postoperative 266.62 (224.57, 326.04) g (P<0.001), the end-diastolic posterior wall thickness of the left ventricle decreased from preoperative 1.30 (1.20, 1.60) cm to postoperative 1.20 (1.18, 1.40) cm (P<0.001), the relative wall thickness decreased from preoperative 0.78 (0.78, 1.02) to postoperative 0.63 (0.56, 0.72) (P<0.001), the end-systolic inner diameter of the left ventricle increased from preoperative (2.91±0.50) cm to postoperative (3.19±0.53) cm (P=0.001), and the end-diastolic inner diameter of the left ventricle increased from preoperative (4.41±0.48) cm to postoperative (4.66±0.52) cm (P=0.005). The left ventricular outflow diameter increased from preoperative (1.28±0.46) cm to postoperative (1.57±0.32) cm (P=0.001), the left ventricular outflow pressure gradient decreased from preoperative 58.50 (40.75, 92.50) mm Hg to postoperative 11.50 (7.75, 20.50) mm Hg (P<0.001), the left ventricular ejection fraction increased from preoperative 60.00% (56.75%, 65.00%) to postoperative 63.00% (62.00%, 66.00%) (P=0.024), and the degree of systolic anterior motion of the mitral valve leaflets decreased (P＜0.001). Conclusion The cardiac function of patients with HOCM is improved after Liwen surgery, myocardial injury marker levels are decreased, cardiac reverse remodeling occurres, and the surgical outcome is good.

ObjectiveTobacco-related diseases remain one of the leading preventable public health challenges worldwide and are among the primary causes of premature death. In recent years, accumulating evidence has supported the classification of nicotine addiction as a chronic brain disease, profoundly affecting both brain structure and function. Despite the urgency, effective diagnostic methods for smoking addiction remain lacking, posing significant challenges for early intervention and treatment. To address this issue and gain deeper insights into the neural mechanisms underlying nicotine dependence, this study proposes a novel graph neural network framework, termed TI-GNN. This model leverages functional magnetic resonance imaging (fMRI) data to identify complex and subtle abnormalities in brain connectivity patterns associated with smoking addiction. MethodsThe study utilizes fMRI data to construct functional connectivity matrices that represent interaction patterns among brain regions. These matrices are interpreted as graphs, where brain regions are nodes and the strength of functional connectivity between them serves as edges. The proposed TI-GNN model integrates a Transformer module to effectively capture global interactions across the entire brain network, enabling a comprehensive understanding of high-level connectivity patterns. Additionally, a spatial attention mechanism is employed to selectively focus on informative inter-regional connections while filtering out irrelevant or noisy features. This design enhances the model’s ability to learn meaningful neural representations crucial for classification tasks. A key innovation of TI-GNN lies in its built-in causal interpretation module, which aims to infer directional and potentially causal relationships among brain regions. This not only improves predictive performance but also enhances model interpretability—an essential attribute for clinical applications. The identification of causal links provides valuable insights into the neuropathological basis of addiction and contributes to the development of biologically plausible and trustworthy diagnostic tools. ResultsExperimental results demonstrate that the TI-GNN model achieves superior classification performance on the smoking addiction dataset, outperforming several state-of-the-art baseline models. Specifically, TI-GNN attains an accuracy of 0.91, an F1-score of 0.91, and a Matthews correlation coefficient (MCC) of 0.83, indicating strong robustness and reliability. Beyond performance metrics, TI-GNN identifies critical abnormal connectivity patterns in several brain regions implicated in addiction. Notably, it highlights dysregulations in the amygdala and the anterior cingulate cortex, consistent with prior clinical and neuroimaging findings. These regions are well known for their roles in emotional regulation, reward processing, and impulse control—functions that are frequently disrupted in nicotine dependence. ConclusionThe TI-GNN framework offers a powerful and interpretable tool for the objective diagnosis of smoking addiction. By integrating advanced graph learning techniques with causal inference capabilities, the model not only achieves high diagnostic accuracy but also elucidates the neurobiological underpinnings of addiction. The identification of specific abnormal brain networks and their causal interactions deepens our understanding of addiction pathophysiology and lays the groundwork for developing targeted intervention strategies and personalized treatment approaches in the future.

Haematitum and Limonitum are two iron-containing mineral medicines included in the 2020 edition of the Chinese Pharmacopoeia. They have similar main components and major differences in their property, flavor, channel tropism, and clinical uses. In this study, we investigated the surface properties, mineral composition, mineral dissociation, elemental composition, and iron state of Haematitum and Limonitum to explore their mineralogical differences. Scanning electron microscopy(SEM), specific surface and porosity analyzer, X-ray diffractometer(XRD), X-ray photoelectron spectrometer(XPS), and advanced mineral identification and characterization system(AMICS) were used to analyze the mineralogy of Haematitum and Limonitum. The results showed that Haematitum had an angular surface with granular attachments and a specific surface area of 17.04 m~2·g~(-1). In comparison, Limonitum had a smooth and flat surface with a bundled acicular crystal structure and a specific surface area of 46.29 m~2·g~(-1). Haematitum consists of 31 detectable minerals containing 18 elements, with the major element, iron(44.5% Fe~(2+) and 55.5% Fe~(3+)) distributed in 17 minerals, including hematite, iron oxide, knebelite, siderite, and magnesioferrite. Limonitum consists of 32 detectable minerals containing 17 elements, with the major element, iron(14.5% Fe~(2+) and 85.5% Fe~(3+)) distributed in 19 minerals, including limonite, iron oxide, chlorite, and knebelite. In summary, the elemental composition of Haematitum and Limonitum does not differ greatly, but there are large differences in the mineral composition and iron state. The large specific surface area and strong adsorption capacity of Limonitum may be one of the mechanisms of its anti-diarrheal action. The Fe_2O_3 and illite contained in Haematitum and Limonitum may be the key substances for their hemostasis effects. The mineralogical differences are expected to provide a reference for explaining the scientific connotation of mineral medicine and laying a material foundation for studying its mechanism of action.
Iron/analysis* ; Minerals/chemistry* ; Drugs, Chinese Herbal/chemistry* ; X-Ray Diffraction ; Microscopy, Electron, Scanning ; Photoelectron Spectroscopy