OBJECTIVE To construct an intelligent pharmaceutical Q&A platform for precision medication with low “artificial intelligence （AI） hallucination”， aiming to enhance the accuracy， consistency， and traceability of medication consultations. METHODS Medication package inserts were batch-processed and converted into structured data through Python programming to build a local pharmaceutical knowledge base. The retrieval and question-answering processes were designed based on large language models， and system integration and localized deployment were completed on Dify platform. By designing typical clinical medication questions and comparing the output of the intelligent pharmaceutical Q&A platform with the online version of DeepSeek across dimensions such as peak time retrieval， half-life， and dosage adjustment reasoning for patients with renal impairment， the accuracy and reliability of its retrieval and reasoning results were evaluated. RESULTS The intelligent pharmaceutical Q&A platform， constructed based on local drug package inserts， achieved 100% accuracy in retrieval and reasoning for peak time， half-life， and dosage adjustment schemes. In comparison， the online version of DeepSeek demonstrated accuracies of 30%（6/20）， 50%（10/20）， and 38%（23/60） across these three dimensions， respectively. CONCLUSIONS The constructed intelligent pharmaceutical Q&A platform is capable of accurately retrieving and extracting information from the local knowledge base based on clinical inquiries， thereby avoiding the occurrence of AI hallucinations and providing reliable medication decision support for healthcare professionals.

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.

Clinical practice guidelines represent the best recommendations for patient care. They are developed through systematically reviewing currently available clinical evidence and weighing the relative benefits and risks of various interventions. However, clinical practice guidelines have to go through a long translation cycle from development and revision to clinical promotion and application, facing problems such as scattered distribution, high duplication rate, and low actual utilization. At present, the clinical practice guideline information platform can directly or indirectly solve the problems related to the lengthy revision cycles, decentralized dissemination and limited application of clinical practice guidelines. Therefore, this paper systematically examines different types of clinical practice guideline information platforms and investigates their corresponding challenges and emerging trends in platform design, data integration, and practical implementation, with the aim of clarifying the current status of this field and providing valuable reference for future research on clinical practice guideline information platforms.

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.

Collagen is a major structural protein in the matrix of animal cells and the most widely distributed and abundant functional protein in mammals. Collagen’s good biocompatibility, biodegradability and biological activity make it a very valuable biomaterial. According to the source of collagen, it can be broadly categorized into two types: one is animal collagen; the other is recombinant collagen. Animal collagen is mainly extracted and purified from animal connective tissues by chemical methods, such as acid, alkali and enzyme methods, etc. Recombinant collagen refers to collagen produced by gene splicing technology, where the amino acid sequence is first designed and improved according to one’s own needs, and the gene sequence of improved recombinant collagen is highly consistent with that of human beings, and then the designed gene sequence is cloned into the appropriate vector, and then transferred to the appropriate expression vector. The designed gene sequence is cloned into a suitable vector, and then transferred to a suitable expression system for full expression, and finally the target protein is obtained by extraction and purification technology. Recombinant collagen has excellent histocompatibility and water solubility, can be directly absorbed by the human body and participate in the construction of collagen, remodeling of the extracellular matrix, cell growth, wound healing and site filling, etc., which has demonstrated significant effects, and has become the focus of the development of modern biomedical materials. This paper firstly elaborates the structure, type, and tissue distribution of human collagen, as well as the associated genetic diseases of different types of collagen, then introduces the specific process of producing animal source collagen and recombinant collagen, explains the advantages of recombinant collagen production method, and then introduces the various systems of expressing recombinant collagen, as well as their advantages and disadvantages, and finally briefly introduces the application of animal collagen, focusing on the use of animal collagen in the development of biopharmaceutical materials. In terms of application, it focuses on the use of animal disease models exploring the application effects of recombinant collagen in wound hemostasis, wound repair, corneal therapy, female pelvic floor dysfunction (FPFD), vaginal atrophy (VA) and vaginal dryness, thin endometritis (TE), chronic endometritis (CE), bone tissue regeneration in vivo, cardiovascular diseases, breast cancer (BC) and anti-aging. The mechanism of action of recombinant collagen in the treatment of FPFD and CE was introduced, and the clinical application and curative effect of recombinant collagen in skin burn, skin wound, dermatitis, acne and menopausal urogenital syndrome (GSM) were summarized. From the exploratory studies and clinical applications, it is evident that recombinant collagen has demonstrated surprising effects in the treatment of all types of diseases, such as reducing inflammation, promoting cell proliferation, migration and adhesion, increasing collagen deposition, and remodeling the extracellular matrix. At the end of the review, the challenges faced by recombinant collagen are summarized: to develop new recombinant collagen types and dosage forms, to explore the mechanism of action of recombinant collagen, and to provide an outlook for the future development and application of recombinant collagen.

Objective To explore the functional connectivity(FC)changes of hippocampus and amygdala in type 2 diabetes mellitus(T2DM)patients with erectile dysfunction(DMED),and the central pathological neural mechanisms underlying DMED.Methods 61 T2DM patients who visited Department of Endocrinology,Nanjing First Hospital,Nanjing Medical University from January 2020 to December 2021 were selected and divided into a simple T2DM group(n=30)and a combined DMED group(n=31).Another 47 healthy individuals were selected as control group(NC).The international erectile function scale(IIEF-5)was used to evaluate the erectile function.Resting-state functional magnetic resonance imaging(rs-fMRI)data were acquired from all participants.MRI data were preprocessed by the DPABI software package.Bilateral hippocampus and amygdala were selected as regions of interest(ROI)and the whole brain FC values were calculated.The FC values of brain regions between groups were tested by two-sample t-test with REST software package.Results Left hippocampus as ROI:compared with the NC group,FC values of the left superior temporal gyrus increased in the T2DM group,FC values of the left superior frontal gyrus,left inferior temporal gyrus,left posterior central gyrus and rectus gyrus decreased in the DMED group.Compared with the T2DM group,FC values of the left inferior parietal gyrus,left supramarginal gyrus,left middle occipital gyrus and right posterior central gyrus decreased in the DMED group.Right hippocampus as ROI:compared with the NC group,FC values of the right middle temporal gyrus and right rolandic operculum increased while FC values of the right calcarine fissure decreased in the T2DM group;FC values of bilateral anterior cingulate gyrus,right middle temporal gyrus and left rectus gyrus decreased in the DMED group.Compared with the T2DM group,FC values of the left middle frontal gyrus,left inferior parietal gyrus and right inferior temporal gyrus decreased in the DMED group.Left amygdala as ROI:compared with the NC group,FC values in the left parahippocampal gyrus,left fusiform gyrus and right insula increased in the T2DM group;FC value of the left middle temporal gyrus decreased in the DMED group.Compared with the T2DM group,FC values of the left middle frontal gyrus and left supramarginal gyrus decreased in the DMED group.Right amygdala as ROI:compared with the NC group,FC values of the left insula,right parahippocampal gyrus,right superior temporal gyrus and right supramarginal gyrus increased while FC values in the right caudate decreased in the T2DM group;FC values of the right middle frontal gyrus,left rectus gyrus and left middle occipital gyrus decreased in the DMED group.Compared with the T2DM group,FC values of the left middle frontal gyrus and left inferior parietal gyrus decreased in the DMED group.Conclusions DMED patients have abnormalities in the hippocampus,amygdala and other brain regions,especially the frontal lobe functional cortex,which may be related to changes in their brain function.

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.

Aim To investigate the pharmacological effects of Kochia scoparia in treating osteoporosis(OP)and explore its therapeutic mechanisms using network pharmacology methods and in vitro experiments.Meth-ods The main chemical components and the targets of Kochia scoparia were screened through literature que-ries and databases such as SwissTargetPrediction.Dis-ease targets for osteoporosis were mined using Gene-Cards and OMIM databases with"osteoporosis"as the keyword,and the intersection of the two was taken to obtain the targets for Kochia scoparia in treating osteo-porosis.The STRING database was applied to construct the core target protein-protein interaction network,the DAVID database was utilized for functional and signa-ling pathway enrichment analysis to further explore the therapeutic effects of Kochia scoparia on osteoporosis and the underlying mechanisms;molecular docking was performed using AutoDock software.Bone marrow mesenchymal stem cells(BMSCs)were cultured in vitro,and the effects of the active components of Kochia scoparia,Zingibroside R1,Chikusetsusaponin IVa,and Momordin Ic,on cell viability were detected by CCK-8.After osteogenic induction,osteogenic differentiation a-bility of BMSCs was detected by alkaline phosphatase staining and alizarin red staining;the expression of os-teogenic-related protein RUNX2 was detected by West-ern blot.Results A total of 573 targets related to Kochia scoparia and 5 774 targets related to osteoporo-sis were screened,with 346 intersection targets between them.KEGG pathway enrichment mainly included cancer pathways,PI3K-AKT signaling pathways,and HIF-1 signaling pathways,etc.The main core targets included TNF,AKT1,SRC,STAT3,EGFR,HIF-1α,etc.The active components of Kochia scoparia signifi-cantly promoted the osteogenic differentiation ability of BMSCs.Conclusions The multi-component,multi-target,and multi-pathway mechanisms of Kochia scopar-ia in the treatment of osteoporosis were preliminarily e-lucidated,providing new ideas for further research on the mechanisms of Kochia scoparia in treating osteopo-rosis.

Objective To study the tongue manifestation of patients with different syndromes in non-small cell lung cancer(NSCLC)and the correlation between tongue characteristics of different syndromes and tumor markers and coagulation indicators.Methods Totally 497 patients with NSCLC were grouped according to syndrome differentiation,and the differences in tongue characteristics of different syndromes were compared.Bivariate correlation analysis was used to study the correlation between tongue characteristics and serum tumor markers and coagulation indicators in patients with NSCLC of different syndromes.Results Compared with healthy people of different syndromes,in TB-a,yin deficiency and phlegm-heat syndrome>healthy group>qi-yin deficiency syndrome>spleen deficiency and phlegm-dampness syndrome>lung stagnation and phlegm-stasis syndrome(P<0.001).In TB-L,healthy group>spleen deficiency and phlegm-dampness syndrome>qi-yin deficiency syndrome>lung stagnation and phlegm-stasis syndrome>yin deficiency and phlegm-heat syndrome(P<0.001).In TB-b,yin deficiency and phlegm-heat syndrome>qi-yin deficiency syndrome>spleen deficiency and phlegm-dampness syndrome>healthy group>lung stagnation and phlegm-stasis syndrome(P<0.001).Yin deficiency and phlegm-heat syndrome had the highest TB-a and the lowest Per-all.Spleen deficiency and phlegm-dampness syndrome had the highest TB-L and Per-all.Lung stagnation and phlegm-stasis syndrome had lower TB-b and TC-b than other groups,lower TB-a than the healthy group,and a high Per-all index(P<0.05).In terms of tumor markers,Per-all in spleen deficiency and phlegm-dampness syndrome was positively correlated with Ca199,Ca50 and Ca242(P<0.05).In terms of coagulation indicators,the tongue texture index of lung stagnation and phlegm-stasis syndrome had a high correlation with the coagulation indicator Fg(P<0.01).Conclusion Different TCM syndromes of NSCLC have their own typical tongue characteristics.Tongue manifestations of different syndromes are correlated with tumor markers and coagulation indicators,respectively,which can reflect changes in clinical status.