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.

In the era of deep technologization with the flourishing development of newquality productive forces， China’s medical science and technology innovation has transitioned from “following” to “leading”， and the ethical governance environment of medical science and technology has undergone profound changes. However， the traditional ethical governance system of medical science and technology faces several issues， such as outdated ethical governance concepts， inadequate ethical norms， excessive hidden ethical risks， and numerous loopholes in governance systems， which fail to effectively respond to the diverse and complex ethical risk challenges. To this end， it is essential to promote the transformation of ethical governance thinking in medical science and technology based on the reality of newquality productivity forces and deep technologization， as well as to shift unilateral， extensive， and single governance into comprehensive， precise， and early-warning governance. Additionally， it is necessary to cultivate an ethical governance concept that prioritizes ethics and prevention， establish a diverse and collaborative ethical governance model， set up a prevention mechanism focused on major ethical risks， as well as enhance the systems of ethical communication， review， and feedback in medical science and technology.

ObjectiveTo investigate the preventive effect and mechanism of Dendrobium officinale （DO） on non-alcoholic fatty liver disease （NAFLD） by network pharmacology and animal experiments. MethodsDO components in blood after administration were identified and analyzed using ultra-performance liquid chromatography-quadrupole-electrostatic field orbitrap high-resolution mass spectrometry （UPLC-QE-HF-MS/MS）. Network pharmacology and molecular docking methods were employed to obtain active ingredients and potential targets of DO for NAFLD control. High-fat feeds were used to replicate the NAFLD rat model. Biochemical kits were used for detecting the expression levels of blood lipids， hepatic lipids， and liver functions of rats. Hematoxylin-eosin （HE） staining and oil red O staining were employed to observe pathological changes in rat liver， and real-time fluorescence quantitative PCR （Real-time PCR） assay was performed to validate potential targets obtained from the network pharmacology analysis. ResultsA total of 13 DO components were identified in blood， including berberine， dihydrosanguinarine， and oxypeucedanin. A total of 14 potential targets were screened through network pharmacology， including Forkhead box protein O1 （FoxO1）， epidermal growth factor receptor （EGFR）， and insulin-like growth factor 1 （IGF-1R）， involving pathways such as the advanced glycation end product （AGE）/receptor for AGE （RAGE） signaling pathway， blood lipids and atherosclerosis， insulin resistance， and FoxO signaling. The results of animal experiments showed that the NAFLD rat model was successfully replicated. After the preventive treatment with DO for NAFLD rats， the indexes of blood lipids， hepatic lipids， and liver function were normalized； lipid deposition and lesions in the liver were significantly improved； the expression level of FoxO1 mRNA in the liver was significantly reduced （P<0.05）， and the mRNA expression levels of phosphatidylinositide 3-kinases （PI3K）， protein kinase B （Akt）， EGFR， and IGF-1R were significantly increased （P<0.05）. ConclusionDO has a preventive effect on NAFLD rats， and the mechanism of action may be related to the modulation of IGF1R and EGFR targets and activation of the PI3K/Akt/FoxO1 signaling pathway.

ObjectiveIn the realm of forensic science, dust is a valuable type of trace evidence with immense potential for intricate investigations. With the development of DNA sequencing technologies, there is a heightened interest among researchers in unraveling the complex tapestry of microbial communities found within dust samples. Furthermore, striking disparities in the microbial community composition have been noted among dust samples from diverse geographical regions, heralding new possibilities for geographical inference based on microbial DNA analysis. The pivotal role of microbial community data from dust in geographical inference is significant, underscoring its critical importance within the field of forensic science. This study aims to delve deeply into the nuances of fungal community composition across the urban landscapes of Beijing, Fuzhou, Kunming, and Urumqi in China. It evaluates the accuracy of biogeographic inference facilitated by the internal transcribed spacer 2 (ITS2) fungal sequencing while concurrently laying a robust foundation for the operational integration of environmental DNA into geographical inference mechanisms. MethodsITS2 region of the fungal genomes was amplified using universal primers known as 5.8S-Fun/ITS4-Fun, and the resulting DNA fragments were sequenced on the Illumina MiSeq FGx platform. Non-metric multidimensional scaling analysis (NMDS) was employed to visually represent the differences between samples, while analysis of similarities (ANOSIM) and permutational multivariate analysis of variance (PERMANOVA) were utilized to statistically evaluate the dissimilarities in community composition across samples. Furthermore, using Linear Discriminant Analysis Effect Size (LEfSe) analysis to identify and filter out species that exhibit significant differences between various cities. In addition, we leveraged SourceTracker to predict the geographic origins of the dust samples. ResultsAmong the four cities of Beijing, Fuzhou, Kunming and Urumqi, Beijing has the highest species richness. The results of species annotation showed that there were significant differences in the species composition and relative abundance of fungal communities in the four cities. NMDS analysis revealed distinct clustering patterns of samples based on their biogeographic origins in multidimensional space. Samples from the same city exhibited clear clustering, while samples from different cities showed separation along the first axis. The results from ANOSIM and PERMANOVA confirmed the significant differences in fungal community composition between the four cities, with the most pronounced distinctions observed between Fuzhou and Urumqi. Notably, the biogeographic origins of all known dust samples were successfully predicted. ConclusionSignificant differences are observed in the fungal species composition and relative abundance among the cities of Beijing, Fuzhou, Kunming, and Urumqi. Employing fungal ITS2 sequencing on dust samples from these urban areas enables accurate inference of biogeographical locations. The high feasibility of utilizing fungal community data in dust for biogeographical inferences holds particular promise in the field of forensic science.

ObjectiveTo investigate the value of third lumbar skeletal muscle mass index （L3-SMI） in predicting the long-term prognosis of patients with acute-on-chronic liver failure （ACLF）， and to provide a useful tool for prognostic scoring of ACLF patients. MethodsA retrospective analysis was performed for the data of 126 patients who underwent abdominal computed tomography （CT） scanning and were diagnosed with ACLF in Shanxi Bethune Hospital from December 2017 to December 2021， including clinical indicators， biochemical parameters， and model for end-stage liver disease （MELD） score， and L3-SMI was calculated. The independent-samples t test was used for comparison of normally distributed continuous data between groups， and the Mann-Whitney U test was used for comparison of non-normally distributed continuous data between groups； the chi-square test was used for comparison of categorical data between groups. The receiver operating characteristic （ROC） curve was used to assess the diagnostic value of L3-SMI and other variables （MELD score and Child-Pugh score）， and the DeLong test was used for comparison of the area under the ROC curve （AUC）. ResultsAmong the 126 patients enrolled， 44 （35%） died within 2 years and 82 （65%） survived. Compared with the survival group， the death group had significantly higher age， incidence rate of ascites， international normalized ratio， MELD score， and Child-Pugh score （all P<0.05） and a significantly lower value of L3-SMI ［38.40 （35.95‍ ‍—‍ ‍46.29） cm²/m² vs 44.19 （40.20‍ ‍—‍ ‍48.58） cm²/m²， Z=-2.855， P=0.004］. L3-SMI had an AUC of 0.720 in predicting 2-year mortality in ACLF patients， with a sensitivity of 63.6% and a specificity of 80.5%， and a combination of L3-SMI， MELD score， and Child-Pugh score had a significantly better AUC than a combination of MELD score and Child-Pugh score in predicting 2-year mortality （0.809 vs 0.757， Z=2.015， P<0.05）. ConclusionL3-SMI has a high predictive value for the prognosis of ACLF patients， and the combination of L3-SMI、MELD score and Child-Pugh score has a higher predictive value for ACLF patients， and the inclusion of L3-SMI or sarcopenia in the conventional prognostic scores of ACLF patients may increase the ability to predict disease progression.

ObjectiveWe reviewed the existing experimental studies about renal injury-inducing Chinese medicine and systematically analyzed the toxicity mechanisms， toxic components， toxicity attenuation measures， and modern evaluation methods of renal injury-inducing Chinese medicine. The results are expected to provide new ideas for the modern research on kidney injury-inducing Chinese medicine， offer new breakthrough points for the toxicity attenuation of Chinese medicine by compatibility and processing， and give insights into the future research of Chinese medicine toxicology on the basis of ensuring the safety and scientific application of Chinese medicine. MethodsThe animal， cell， and clinical studies of kidney injury-inducing Chinese medicine were retrieved from CNKI， Wanfang Data， VIP， PubMed， and Web of Science. The names and toxic components of renal injury-inducing Chinese medicine， renal injury sites， toxicity mechanisms， toxicity attenuation measures， and related evaluation methods were summarized. ResultsThe toxicity mechanisms of kidney injury-inducing Chinese medicine mainly involved oxidative stress， endoplasmic reticulum stress， inflammatory cell infiltration， and organic anion transporters. Processing and compatibility were the main toxicity attenuation measures. The evaluation methods encompassed animal experiments， cell models， network pharmacology， metabolomics， toxicology genomics， and fluorescent probe technology. ConclusionAt present， the toxicological verification of kidney injury-inducing Chinese medicine starts from toxic components and combines various experimental methods， which is more comprehensive and systematic than the previous studies based on only animal experiments. According to the classical theories of traditional Chinese medicine， the toxicity of kidney injury-inducing Chinese medicine is mainly attenuated by decocting in water， steaming， and frying. With the progress of science and technology， new processing methods for toxicity attenuation are emerging， and structural transformation， fermentation， and microwave methods are the key research directions of toxicity attenuation of Chinese medicine in recent years.

Dysphagia is a common complication of stroke. Combining the principles of traditional Chinese medicine with modern research findings， it is proposed that "latent pathogen in the cerebral collaterals" constitutes the core pathogenesis of post-stroke dysphagia （PSD）. In clinical practice， treatment is tailored according to the location of PSD. During the oral stage， when the pathogen invades the face and mouth， resulting in excessive salivation， acupoints are primarily selected from the foot shaoyin （少阴） kidney channel， in combination with ren mai （任脉） ， du mai （督脉）， chong mai （冲脉） and the spleen channel， to replenish essence and fill the marrow， dispel dampness and unblock the channels. In the pharyngeal stage， as the pathogen obstructs the throat， disrupting normal swallowing， the therapy emphasizes dredging the shaoyang （少阳） channel and warming and tonifying the jueyin （厥阴） channel， by taking acupoints mainly from the hand and foot shaoyang channels， along with the jueyin channels， so as to soothe the liver and promote bile secretion， regulate and harmonize qi and blood. During the esophageal stage， where the pathogen damages the esophagus， impeding food passage， the treatment emphasizes activating the yangming （阳明） channels and regulating taiyin （太阴） channels； acupoints are mainly selected from the foot yangming stomach channel， along with the taiyin channels， aiming to warm yang， unblock the channels and dispel stasis.

ObjectiveWe reviewed the existing experimental studies about renal injury-inducing Chinese medicine and systematically analyzed the toxicity mechanisms， toxic components， toxicity attenuation measures， and modern evaluation methods of renal injury-inducing Chinese medicine. The results are expected to provide new ideas for the modern research on kidney injury-inducing Chinese medicine， offer new breakthrough points for the toxicity attenuation of Chinese medicine by compatibility and processing， and give insights into the future research of Chinese medicine toxicology on the basis of ensuring the safety and scientific application of Chinese medicine. MethodsThe animal， cell， and clinical studies of kidney injury-inducing Chinese medicine were retrieved from CNKI， Wanfang Data， VIP， PubMed， and Web of Science. The names and toxic components of renal injury-inducing Chinese medicine， renal injury sites， toxicity mechanisms， toxicity attenuation measures， and related evaluation methods were summarized. ResultsThe toxicity mechanisms of kidney injury-inducing Chinese medicine mainly involved oxidative stress， endoplasmic reticulum stress， inflammatory cell infiltration， and organic anion transporters. Processing and compatibility were the main toxicity attenuation measures. The evaluation methods encompassed animal experiments， cell models， network pharmacology， metabolomics， toxicology genomics， and fluorescent probe technology. ConclusionAt present， the toxicological verification of kidney injury-inducing Chinese medicine starts from toxic components and combines various experimental methods， which is more comprehensive and systematic than the previous studies based on only animal experiments. According to the classical theories of traditional Chinese medicine， the toxicity of kidney injury-inducing Chinese medicine is mainly attenuated by decocting in water， steaming， and frying. With the progress of science and technology， new processing methods for toxicity attenuation are emerging， and structural transformation， fermentation， and microwave methods are the key research directions of toxicity attenuation of Chinese medicine in recent years.

Multiple system atrophy (MSA) is a rare neurodegenerative disease with complex clinical manifestations, presenting substantial challenges in clinical diagnosis and treatment. Its symptoms and the eight extraordinary meridians are potentially correlated; therefore, this article explores the association between MSA symptom clusters and the eight extraordinary meridians based on their circulation and physiological functions, as well as their treatment strategies. The progression from deficiency to damage in the eight extraordinary meridians aligns with the core pathogenesis of MSA, which is characterized by "the continuous accumulation of impacts from the vital qi deficiency leading to eventual damage". Liver and kidney deficiency and the emptiness of the eight extraordinary meridians are required for the onset of MSA; the stagnation of qi deficiency and the gradual damage to the eight extraordinary meridians are the key stages in the prolonged progression of MSA. The disease often begins with the involvement of the yin and yang qiao mai, governor vessel, thoroughfare vessel, and conception vessel before progressing to multiple meridian involvements, ultimately affecting all eight extraordinary meridians simultaneously. The treatment approach emphasizes that "the direct method may be used for joining battle, but indirect method will be needed in order to secure victory" and focuses on "eliminate pathogenic factors and reinforce healthy qi". Distinguishing the extraordinary meridians and focusing on the primary symptoms are pivotal to improving efficacy. Clinical treatment is aimed at the target, and tailored treatment based on careful clinical observation ensures precision in targeting the disease using the eight extraordinary meridians as the framework and core symptoms as the specific focus. Additionally, combining acupuncture, daoyin therapy, and other method may help prolong survival. This article classifies clinical manifestations based on the theory of the eight extraordinary meridians and explores treatment.

ObjectiveThe rapid advancement of bioanalytical technologies has heightened the demand for high-throughput, label-free, and real-time cellular analysis. Electrochemical impedance spectroscopy (EIS) operating in the GHz frequency range (GHz-EIS) has emerged as a promising tool for characterizing cell suspensions due to its ability to rapidly and non-invasively capture the dielectric properties of cells and their microenvironment. Although GHz-EIS enables rapid and label-free detection of cell suspensions, significant challenges remain in interpreting GHz impedance data for complex samples, limiting the broader application of this technique in cellular research. To address these challenges, this study presents a novel method that integrates GHz-EIS with deep learning algorithms, aiming to improve the precision of cell suspension concentration identification and quantification. This method provides a more efficient and accurate solution for the analysis of GHz impedance data. MethodsThe proposed method comprises two key components: dielectric property dataset construction and backpropagation (BP) neural network modeling. Yeast cell suspensions at varying concentrations were prepared and separately introduced into a coaxial sensor for impedance measurement. The dielectric properties of these suspensions were extracted using a GHz-EIS dielectric property extraction method applied to the measured impedance data. A dielectric properties dataset incorporating concentration labels was subsequently established and divided into training and testing subsets. A BP neural network model employing specific activation functions (ReLU and Leaky ReLU) was then designed. The model was trained and tested using the constructed dataset, and optimal model parameters were obtained through this process. This BP neural network enables automated extraction and analytical processing of dielectric properties, facilitating precise recognition of cell suspension concentrations through data-driven training. ResultsThrough comparative analysis with conventional centrifugal methods, the recognized concentration values of cell suspensions showed high consistency, with relative errors consistently below 5%. Notably, high-concentration samples exhibited even smaller deviations, further validating the precision and reliability of the proposed methodology. To benchmark the recognition performance against different algorithms, two typical approaches—support vector machines (SVM) and K-nearest neighbor (KNN)—were selected for comparison. The proposed method demonstrated superior performance in quantifying cell concentrations. Specifically, the BP neural network achieved a mean absolute percentage error (MAPE) of 2.06% and an R² value of 0.997 across the entire concentration range, demonstrating both high predictive accuracy and excellent model fit. ConclusionThis study demonstrates that the proposed method enables accurate and rapid determination of unknown sample concentrations. By combining GHz-EIS with BP neural network algorithms, efficient identification of cell concentrations is achieved, laying the foundation for the development of a convenient online cell analysis platform and showing significant application prospects. Compared to typical recognition approaches, the proposed method exhibits superior capabilities in recognizing cell suspension concentrations. Furthermore, this methodology not only accelerates research in cell biology and precision medicine but also paves the way for future EIS biosensors capable of intelligent, adaptive analysis in dynamic biological research.