Background: Alzheimer’s disease (AD) is the most prevalent neurodegenerative disorder. Cellular drug screening represents a key approach in the preclinical discovery of AD therapeutics. Moreover, selecting an appropriate cellular model is essential for exploring the mechanisms underlying AD pathogenesis. Objective: This study aimed to establish a progressive strategy integrating cell model construction, monomer evaluation, and effective component group-based drug discovery for the development of novel therapeutics targeting AD. Methods: A novel AD12 cell line stably expressing the double-transgenic genes amyloid precursor protein (APP)695/presenilin 1(PS1)-ΔE9 was first constructed and subjected to lipopolysaccharide (LPS) stimulation. The resulting LPS-induced neuroinflammatory response was characterized using metabolomic analysis. Subsequently, 16 alkaloids derived from traditional Chinese medicine(TCM) were screened with the LPS-AD12 cell model. Molecular docking was then performed to assess the binding affinity of benzoylaconitine (BAC) with APP and PS1 proteins. A targeted metabolomics approach focusing on amino acids and the tricarboxylic acid (TCA) cycle was applied to BAC-treated LPS-AD12 cells. Finally, aconite extract was administered to five-familial-AD-mutations(5xFAD) transgenic mice, and therapeutic efficacy was evaluated through phenotypic and metabolomic analyses. Results: LPS stimulation induced neuroinflammation in AD12 cells, characterized by elevated levels of interleukin-6, amyloid-β (Aβ ), and PS1. The primary metabolic pathways affected in AD12 cells included alanine, aspartate, and glutamate metabolism, as well as arginine biosynthesis. Notably, BAC significantly reduced the levels of Aβ and interleukin-6 in LPS-AD12 cells. Furthermore, molecular docking analyses revealed a strong binding affinity of BAC with APP and PS1 proteins. Targeted metabolomics analysis indicated that the pharmacological activity of BAC was primarily associated with its anti-inflammatory effects, modulation of the cholinergic signaling pathway, and regulation of energy metabolism. Behavioral experiments in 5xFAD mice, together with immunofluorescence assessments of brain tissues (amyloid-β, glial fibrillary acidic protein, and ionized calcium-binding adapter molecule 1), demonstrated that aconite extract treatment significantly alleviated AD-related symptoms. In addition, metabolomics-based mechanistic analyses revealed that serine, acetylcholine, ornithine, and gamma-aminobutyric acid exhibited consistent trends in both brain tissue and serum samples from treated mice. Conclusion: This study established a novel AD12 cell model and an effective, reliable LPS-induced cell-based screening system. Additionally, we proposed a new drug discovery strategy integrating cell model construction, monomer evaluation, and effective component group-based drug discovery. This screening system has the potential to accelerate the identification of anti-AD agents and provides a feasible framework for subsequent in-depth investigations into new drug development from TCM, thereby contributing to the modernization of TCM-derived therapeutics.

Objective:To investigate the risk factors associated with post-prematurity respiratory disease (PPRD) in very preterm infants.Methods:A prospective cohort study was conducted, enrolling 369 very preterm infants who were admitted to the neonatal intensive care unit of Xinhua Hospital, Shanghai Jiao Tong University School of Medicine, within one week of birth from January 2019 to June 2023. Data on maternal and infant clinical characteristics, neonatal morbidities, and treatments during hospitalization were collected. The very preterm infants were divided into 2 groups based on whether they developed PPRD. Continuous variables were compared using Mann-Whitney U test, while categorical variables were compared using χ2 tests or continuity correction χ2 test. Multivariate Logistic regression analysis was used to identify the independent risk factors for PPRD in very preterm infants. Results:Among the 369 very preterm infants, 217 cases(58.8%) were male, with a gestational age of 30 (28, 31) weeks at birth and a birth weight of 1 320 (1 085, 1 590) g. Of these, 116 cases (31.4%) developed PPRD, while 253 cases (68.6%) did not. The very preterm infants in the PPRD group had a lower gestational age and lower birth weight (both, P<0.001). The PPRD group also had a higher proportion of males, lower Apgar scores at the 1 th minute after birth and the 5 th minutes after birth, a higher rate of born via cesarean delivery, and a higher incidence of bronchopulmonary dysplasia, more pulmonary surfactant treatment, longer durations of mechanical ventilation, longer total oxygen therapy, and lower Z-score for weight at discharge (all P<0.05). Multivariate Logistic regression analysis showed that gestational age ( OR=0.85, 95% CI 0.73-0.99, P=0.037), born via cesarean delivery ( OR=2.23, 95% CI 1.21-4.10, P=0.010), a duration of mechanical ventilation ≥7 days ( OR=2.51, 95% CI 1.43-4.39, P=0.001), and a Z-score for weight at discharge ( OR=0.82, 95% CI 0.67-0.99, P=0.040) were all independent risk factors for PPRD in very preterm infants. Conclusion:Very preterm infants with a small gestational age, born via cesarean section, mechanical ventilation ≥7 days, and a low Z-score for weight at discharge should be closely monitored for PPRD, and provided with standardized respiratory management after discharge.

Advancements in artificial intelligence (AI) and emerging technologies are rapidly expanding the exploration of chemical space, facilitating innovative drug discovery. However, the transformation of novel compounds into safe and effective drugs remains a lengthy, high-risk, and costly process. Comprehensive early-stage evaluation is essential for reducing costs and improving the success rate of drug development. Despite this need, no comprehensive tool currently supports systematic evaluation and efficient screening. Here, we present druglikeFilter, a deep learning-based framework designed to assess drug-likeness across four critical dimensions: 1) physicochemical rule evaluated by systematic determination, 2) toxicity alert investigated from multiple perspectives, 3) binding affinity measured by dual-path analysis, and 4) compound synthesizability assessed by retro-route prediction. By enabling automated, multidimensional filtering of compound libraries, druglikeFilter not only streamlines the drug development process but also plays a crucial role in advancing research efforts towards viable drug candidates, which can be freely accessed at https://idrblab.org/drugfilter/.

Objective To survey the awareness and intended adoption of patient-based real-time quality control(PBRTQC)among medical laboratories,thereby providing a basis for subsequent research and promotion efforts.Methods An electronic questionnaire was distributed via the Questionnaire Star system to collect participants' general information,their knowledge,attitudes,and practices regarding PBRTQC,as well as their implementation willingness.Results A total of 161 valid questionnaires were collected.The sur-vey revealed that fewer than 50％of laboratory staff had basic knowledge of PBRTQC,and their confidence in establishing and applying PBRTQC in their own laboratories was low.However,they acknowledged its potential to enhance quality management.Key concerns and support needs for PBRTQC promotion include professional implementation guidelines and policy support,reliable third-party evalu-ations,software and hardware support,and user training.Conclusion The laboratory staff accepted the value of PBRTQC and gener-ally held a positive attitude toward its application.Future efforts should focus on developing standardized guidelines,refining evaluation methods,advancing software and hardware,and enhancing knowledge dissemination,technical training and other actions related to guiding the practical implementation thereby facilitating the wider adoption of PBRTQC.

Advancements in artificial intelligence(AI)and emerging technologies are rapidly expanding the exploration of chemical space,facilitating innovative drug discovery.However,the transformation of novel compounds into safe and effective drugs remains a lengthy,high-risk,and costly process.Comprehensive early-stage evaluation is essential for reducing costs and improving the success rate of drug development.Despite this need,no comprehensive tool currently supports systematic evaluation and efficient screening.Here,we present druglikeFilter,a deep learning-based framework designed to assess drug-likeness across four critical dimensions:1)physicochemical rule evaluated by systematic determination,2)toxicity alert investigated from multiple perspectives,3)binding affinity measured by dual-path analysis,and 4)compound synthesizability assessed by retro-route prediction.By enabling automated,multidimensional filtering of compound libraries,druglikeFilter not only streamlines the drug development process but also plays a crucial role in advancing research efforts towards viable drug candidates,which can be freely accessed at https://idrblab.org/drugfilter/.

ObjectiveTo explore the differences in the accumulation of secondary metabolites of Dendrobium nobile cultivated on epiphytic stones and trees， so as to elucidate the scientific connotation of "only those that grow on stones has superior quality"， and provide a direction for the cultivation and quality evaluation of D. nobile. MethodsUltra-performance liquid chromatography-triple quadrupole/linear ion trap mass spectrometry（UPLC-QTRAP-MS/MS）-based widely targeted metabolomics was used to detect the metabolites of D. nobile cultivated on epiphytic stones and trees. And the combination of principal component analysis（PCA）， hierarchical cluster analysis（HCA）， and orthogonal partial least squares-discriminant analysis（OPLS-DA） was performed for multivariate statistical analysis of metabolites. Differential metabolites were screened by variable importance in the projection（VIP） value≥1 and log₂fold change（FC）≥1 or ≤-1， and Kyoto Encyclopedia of Genes and Genomes（KEGG） enrichment analysis was conducted. ResultsA total of 1 267 metabolites were identified in the stems of D. nobile from the two cultivation modes， dominated by flavonoids（292）， phenolic acids（284）， and alkaloids（189）. Through OPLS-DA screening， 473 differential metabolites were obtained. Compared to epiphytic tree-cultivated D. nobile， epiphytic stone-cultivated D. nobile exhibited upregulation of flavonoids， phenolic acids， alkaloids， lignans and coumarins， while quinones and terpenoids were down-regulated. The differential metabolites mainly included flavonoid glycosides and alkaloids， and these differential metabolites significantly contributed to characterizing the two cultivation patterns. KEGG enrichment analysis revealed significant enrichment in pathways of flavone and flavonol biosynthesis， flavonoid biosynthesis， tyrosine metabolism， and phenylalanine metabolism in epiphytic stone-cultivated D. nobile. ConclusionEpiphytic stone cultivation is beneficial for the accumulation of phenolic acids， flavonoids， and alkaloids in D. nobile， indicating that the "only those that grow on stones has superior quality" documented in the materia medica has certain scientific basis， and the findings also provide a reference for quality evaluation and discrimination research between epiphytic stone and tree cultivated D. nobile.

ObjectiveTo establish the multi-technique characteristic profiles of Alumen by X-ray diffraction（XRD）， Fourier-transform infrared spectroscopy（FTIR） and thermogravimetric-differential thermal analysis（TG-DTA）， and to explore the spectral characteristics for rapid identification of Alumen and its potential adulterant， Ammonium alum. MethodsA total of 27 batches of Alumen samples from 8 production regions were collected for preliminary identification based on visual characteristics. The PDF standard cards of XRD were used to differentiate Alumen from A. alum， and the XRD characteristic profiles of Alumen were established， and then the common peaks were screened. Based on hierarchical clustering analysis（HCA） and orthogonal partial least squares-discriminant analysis（OPLS-DA）， the characteristic information that could be used for identification of Alumen was selected with variable importance in the projection（VIP） value>1. FTIR characteristic profiles of Alumen were established， and key wavenumbers for identification were screened by HCA and OPLS-DA with VIP value>1. Meanwhile， the thermogravimetric differences between Alumen and A. alum were analyzed by TG-DTA， and the thermogravimetric traits that could be used for identification were screened. ResultsAlumen and A. alum could not be effectively distinguished by traits alone. However， by comparing the PDF standard cards of XRD， 15 batches of Alumen and 12 batches of A. alum could be distinguished. In the XRD profiles， 10 characteristic peaks were confirmed， corresponding to diffraction angles of 14.560°， 24.316°， 12.620°， 32.122°， 17.898°， 34.642°， 27.496°， 46.048°， 40.697° and 21.973°. In the FTIR profiles， 4 wavenumber ranges（399.193-403.050， 1 186.010-1 471.420， 1 801.190-2 620.790， 3 612.020-3 997.710 cm^-1） and 12 characteristic wavenumbers（1 428.994， 1 430.922， 1 432.851， 1 434.779， 1 436.708， 1 438.636， 1 440.565， 1 442.493， 1 444.422， 1 446.350， 1 448.279， 1 450.207 cm^-1） were identified. In the TG-DTA profiles， there were characteristic decomposition peaks of ammonium ion and mass reduction features near 555.34 ℃ for A. alum. These characteristics could serve as important criteria for distinguishing the authenticity of Alumen. ConclusionXRD， FTIR and TG-DTA can be used to rapidly detect Alumen and A. alum， and combined with the discriminant features selected through chemometrics， the rapid and accurate identification of Alumen and A. alum can be achieved. The research findings provide new approaches for the rapid identification of Alumen.

ObjectiveTo investigate the processing technology of calcined Haematitum based on the concept of quality by design（QbD） and to assess its health risk. MethodsTaking whole iron content， Fe²⁺ dissolution content and looseness as critical quality attributes（CQAs）， and calcination temperature， calcination time， spreading thickness and particle size as critical process parameters（CPPs） determined by the failure mode and effect analysis（FMEA）， the processing technology of calcined Haematitum was optimized by orthogonal test combined with analytic hierarchy process-criteria importance through intercriteria correlation（AHP-CRITIC） hybrid weighting method. The contents of heavy metals and harmful elements were determined by inductively coupled plasma mass spectrometry， and the health risk assessment was carried out by daily exposure（EXP）， target hazard quotient（THQ） and lifetime cancer risk（LCR）， and the theoretical value of the maximum limit was deduced. ResultsThe optimal processing technology for calcined Haematitum was calcination at 650 ℃， calcination time of 1 h， particle size of 0.2-0.5 cm， spreading thickness of 1 cm， and vinegar quenching for 1 time［Haematitum-vinegar（10：3）］. The contents of 5 heavy metals and harmful elements in 13 batches of calcined Haematitum were all decreased with reductions of up to 5-fold. The cumulative THQ of 2 batches of samples was>1， while the cumulative THQ of all batches of Haematitum was>1. The LCR of As in 1 batches of Haematitum was 1×10^-6-1×10^-4， and the LCR of the rest was<1×10^-6， and the LCRs of calcined Haematitum were all<1×10^-6， indicating that the carcinogenic risk of calcined Haematitum was low， but special attention should still be paid to Haematitum medicinal materials. Preliminary theoretical values of the maximum limits of Cu， As， Cd， Pb and Hg were formulated as 1 014， 25， 17， 27， 7 mg·kg^-1. ConclusionThe optimized processing technology of calcined Haematitum is stable and feasible， and the contents of heavy metals and harmful elements are reduced after processing. Preliminary theoretical values of the maximum limits of Cu， As， Cd， Pb and Hg are formulated to provide a scientific basis for the formulation of standards for the limits of harmful elements in Haematitum.

ObjectiveBased on the concept of quality by design（QbD）， the processing process of calcined Pyritum was optimized， and its X-ray diffraction（XRD） fingerprint was established. MethodsThe safety， effectiveness and quality controllability of calcined Pyritum were taken as the quality profile（QTPP）， the color， hardness， metallic luster， phase composition， the contents of heavy metals and hazardous elements were taken as the critical quality attributes（CQAs）， and the calcination temperature， calcination time， paving thickness and particle size were determined as the critical process parameters（CPPs）. Differential thermal analysis， X-ray diffraction（XRD） and inductively coupled plasma mass spectrometry（ICP-MS） were used to analyze the correlation between the calcination temperature and CQAs of calcined Pyritum. Then， based on the criteria importance through intercriteria correlation（CRITIC）-entropy weight method， the optimal processing process of calcined Pyritum was optimized by orthogonal test. Powder XRD was used to analyze the phase of calcined Pyritum samples processed according to the best process， and the mean and median maps of calcined Pyritum were established by the superposition of geometric topological figures， and similarity evaluation and cluster analysis were carried out. ResultsThe results of single factor experiments showed that the physical phase of Pyritum changed from FeS₂ to Fe₇S₈ during the process of temperature increase， the color gradually deepened from dark yellow， and the contents of heavy metals and harmful elements decreased. The optimized processing process of calcined Pyritum was as follows：calcination temperature at 750 ℃， calcination time of 2.5 h， paving thickness of 3 cm， particle size of 0.8-1.2 cm， vinegar quenching 1 time［Pyritum-vinegar（10∶3）］. After calcination， the internal structure of Pyritum was honeycomb-shaped， which was conducive to the dissolution of active ingredients. XRD fingerprints of 13 batches of calcined Pyritum characterized by 10 common peaks were established. The similarities of the relative peak intensities of the XRD fingerprints of the analyzed samples were>0.96， and it could effectively distinguish the raw products and unqualified products. ConclusionTemperature is the main factor affecting the quality of calcined Pyritum. After processing， the dissolution of the effective components in Pyritum increases， and the contents of heavy metals and harmful substances decrease， reflecting the function of processing to increase efficiency and reduce toxicity. The optimized processing process is stable and feasible， and the established XRD fingerprint can be used as one of the quality control standards of calcined Pyritum.

ObjectiveTo explore the quantity-quality transfer process of medicinal materials， decoction pieces and standard decoction of Haliotidis Concha（Haliotis discus hannai） by analyzing the physical phase and compositional changes， so as to provide references for the effective control of its quality. MethodsA total of 20 batches of Haliotidis Concha（H. discus hannai） from different habitats were collected and prepared into corresponding calcined products and standard decoction， and the content of CaCO₃ of the three samples were determined and the extract yield and transfer rate of CaCO₃ were calculated. The changes in elemental composition and their relative contents were investigated by X-ray fluorescence spectrometry（XRF）， X-ray diffraction（XRD） was used to study the changes in the phase compositions of the three samples and to establish their respective XRD specific chromatogram. Fourier transform infrared spectrometry（FTIR） was used to study the changes in the chemical composition and content changes of the three samples and to establish their respective FTIR specific chromatogram， while combining hierarchical cluster analysis（HCA）， principal component analysis（PCA） and orthogonal partial least squares-discriminant analysis（OPLS-DA） to find the common and differential characteristics， in order to explore the quantity-quality transfer relationship in the preparation process of standard decoction of Haliotidis Concha（H. discus hannai）. ResultsThe CaCO₃ contents of the 20 batches of medicinal materials， decoction pieces and standard decoction of Haliotidis Concha（H. discus hannai） were 93.87%-98.95%， 96.02%-99.97% and 38.29%-51.96%， respectively， and the extract yield of standard decoction was 1.71%-2.37%， and the CaCO₃ transfer rate of decoction pieces-standard decoction was 0.68%-1.27%. XRF results showed that the elemental species and their relative contents contained in Haliotidis Concha and its calcined products had a high degree of similarity， and although there was no obvious difference in the elemental species contained in decoction pieces and standard decoction， the difference in the relative contents was obvious， which was mainly reflected in the decrease of the relative content of element Ca and the increase of the relative content of element Na. XRD results showed that Haliotidis Concha mainly contained CaCO₃ of aragonite and calcite， while calcined Haliotidis Concha only contained CaCO₃ of calcite， and standard decoction mainly contained CaCO₃ of calcite and Na₂CO₃ of natrite. FTIR results showed that there were internal vibrations of O-H， C-H， C=O， HCO₃^- and CO₃^2- groups in Haliotidis Concha， while O-H， HCO₃^- and CO₃^2- groups existed in the calcined products and standard decoction. ConclusionThe changes of Haliotidis Concha and calcined Haliotidis Concha are mainly the increase of CaCO₃ content， the transformation of CaCO₃ aragonite crystal form to calcite crystal form and the absence of organic components after calcination， and the changes of calcined products and standard decoction are mainly the decrease of CaCO₃ content and the increase of Na₂CO₃ relative content. The method established in the study is applicable to the quality control of the shellfish medicines-decoction pieces- standard decoction， which provides a new idea for the study of quality control of dispensing granules of shellfish medicines.