BACKGROUND:It has been found that mitochondrial function is abnormal in patients with chronic fatigue syndrome,and the administration of coenzymes can improve the symptoms.Warm acupuncture is one of the most important treatments for this disease,but its mechanism of action is unclear. OBJECTIVE:To investigate the effects of warm acupuncture on the phosphatase and tensin inducible kinase 1(PINK1)/Parkin pathway in the skeletal muscle of rats with chronic fatigue syndrome. METHODS:After 3 days of adaptive feeding,32 male Sprague-Dawley rats were randomly divided into normal control,model,warm acupuncture,and coenzyme Q groups with 8 rats in each group.The chronic fatigue syndrome model was established by multiple factors,including swimming exhaustion,chronic immobilization and fasting.After successful modeling,the normal group and the model group were treated with the same fixation and gavage procedures,and the warm acupuncture group was treated with acupuncture at Guanyuan,Zhongwan and Zusanli(bilateral)points,once a day.After the needling was inserted,the moxa pillar was put on the needle handle and ignited,three sessions once.The coenzyme Q group was given 1 mL/kg coenzyme by gavage,once a day for 14 days.The body mass,exhaustive swimming time and food utilization rate during the treatment were recorded.After the treatment,the bilateral gastrocnemius muscles of rats in each group were collected.The pathological morphology of the gastrocnemius muscle was observed by hematoxylin-eosin staining,the mitochondrial morphology and autophagosome of the gastrocnemius muscle were observed by transmission electron microscope.The expression level of microtubule-associated protein light chain 3(LC3)Ⅱ protein in the skeletal muscle was detected by immunohistochemistry.Western blot was used to detect the expression of PINK1,Parkin,LC3 Ⅰ,and LC3 Ⅱ in the skeletal muscle. RESULTS AND CONCLUSION:Compared with the normal group,the gastrocnemius muscle nuclei of the model group were pyknotic,condensed,the number of cells was increased,the cells were arranged disorderly,and the fibers in the gastrocnemius muscle were tightly arranged in the model group.Compared with the model group,the intercellular space became smaller,the nuclei were reduced,and the cell arrangement was orderly in the warm acupuncture group and coenzyme Q group.Compared with the normal group,the skeletal muscle mitochondria in the model group were swollen,fused,and vacuolated seriously,the membrane was partially broken,the matrix was more dissolved,the cristae was broken and disappeared,and autophagy appeared.Compared with the model group,the number of mitochondria increased,the arrangement was relatively neat,mitochondrial vacuolization and rupture of cristae in the gastrocnemius muscle were improved,the membrane structure was relatively intact,and autophagy occurred.Compared with the normal group,the expression of PINK1 protein in the skeletal muscle of the model group was significantly increased(P<0.05),while the expression of Parkin,LC3 Ⅱ and LC3 Ⅱ/Ⅰ protein was slightly upregulated(P>0.05).Compared with the model group,the protein expressions of PINK1,Parkin,LC3 Ⅱ and LC3 Ⅱ/Ⅰ were significantly upregulated in the warm acupuncture and coenzyme Q groups(P<0.05),and the up-regulation was more significant in the warm acupuncture group.To conclude,warm acupuncture can play a role in the treatment of chronic fatigue syndrome by activating the PINK1/Parkin pathway,upregulating LC3 Ⅱ expression,forming mitochondrial autophagosomes,promoting the degradation of damaged mitochondria,and improving mitochondrial quality.

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.

Lactylation, a recently identified post-translational modification of proteins, is induced by lactic acid and can occur at multiple lysine residues in both histone and non-histone proteins. This modification plays a role in disease pathogenesis by affecting transcriptional regulation, mitochondrial metabolism, and immune inflammation. Significant advancements have been made in understanding the mechanisms of lactylation in various ophthalmic diseases, including retinal neovascularization, uveitis, melanoma, and myopia. This paper provides a comprehensive review of the relationship between lactic acid and lactylation, the regulatory mechanisms of lactylation, and the role of lactylation in different ocular diseases. Additionally, it addresses current research limitations and future directions, which is of great significance to elucidate the molecular mechanisms of lactylation in eye diseases and improving the diagnosis and targeted treatment of these conditions.

Adipose tissue is a critical energy reservoir in animals and humans, with multifaceted roles in endocrine regulation, immune response, and providing mechanical protection. Based on anatomical location and functional characteristics, adipose tissue can be categorized into distinct types, including white adipose tissue (WAT), brown adipose tissue (BAT), beige adipose tissue, and pink adipose tissue. Traditionally, adipose tissue research has centered on its morphological and functional properties as a whole. However, with the advent of single-cell transcriptomics, a new level of complexity in adipose tissue has been unveiled, showing that even under identical conditions, cells of the same type may exhibit significant variation in morphology, structure, function, and gene expression——phenomena collectively referred to as cellular heterogeneity. Single-cell transcriptomics, including techniques like single-cell RNA sequencing (scRNA-seq) and single-nucleus RNA sequencing (snRNA-seq), enables in-depth analysis of the diversity and heterogeneity of adipocytes at the single-cell level. This high-resolution approach has not only deepened our understanding of adipocyte functionality but also facilitated the discovery of previously unidentified cell types and gene expression patterns that may play key roles in adipose tissue function. This review delves into the latest advances in the application of single-cell transcriptomics in elucidating the heterogeneity and diversity within adipose tissue, highlighting how these findings have redefined the understanding of cell subpopulations within different adipose depots. Moreover, the review explores how single-cell transcriptomic technologies have enabled the study of cellular communication pathways and differentiation trajectories among adipose cell subgroups. By mapping these interactions and differentiation processes, researchers gain insights into how distinct cellular subpopulations coordinate within adipose tissues, which is crucial for maintaining tissue homeostasis and function. Understanding these mechanisms is essential, as dysregulation in adipose cell interactions and differentiation underlies a range of metabolic disorders, including obesity and diabetes mellitus type 2. Furthermore, single-cell transcriptomics holds promising implications for identifying therapeutic targets; by pinpointing specific cell types and gene pathways involved in adipose tissue dysfunction, these technologies pave the way for developing targeted interventions aimed at modulating specific adipose subpopulations. In summary, this review provides a comprehensive analysis of the role of single-cell transcriptomic technologies in uncovering the heterogeneity and functional diversity of adipose tissues.

Disorders of consciousness (DOC) are pathological conditions characterized by severely suppressed brain function and the persistent interruption or loss of consciousness. Accurate diagnosis and evaluation of DOC are prerequisites for precise treatment. Traditional assessment methods are primarily based on behavioral scales, which are inherently subjective and rely on observable behaviors. Moreover, traditional methods have a high misdiagnosis rate, particularly in distinguishing minimally conscious state (MCS) from vegetative state/unresponsive wakefulness syndrome (VS/UWS). This diagnostic uncertainty has driven the exploration of objective, reliable, and efficient assessment tools. Among these tools, electroencephalography (EEG) has garnered significant attention for its non-invasive nature, portability, and ability to capture real-time neurodynamics. This paper systematically reviews the application of EEG biomarkers in DOC assessment. These biomarkers are categorized into 3 main types: resting-state EEG features, task-related EEG features, and features derived from transcranial magnetic stimulation-EEG (TMS-EEG). Resting-state EEG biomarkers include features based on spectrum, microstates, nonlinear dynamics, and brain network metrics. These biomarkers provide baseline representations of brain activity in DOC patients. Studies have shown their ability to distinguish different levels of consciousness and predict clinical outcomes. However, because they are not task-specific, they are challenging to directly associate with specific brain functions or cognitive processes. Strengthening the correlation between resting-state EEG features and consciousness-related networks could offer more direct evidence for the pathophysiological mechanisms of DOC. Task-related EEG features include event-related potentials, event-related spectral modulations, and phase-related features. These features reveal the brain’s responses to external stimuli and provide dynamic information about residual cognitive functions, reflecting neurophysiological changes associated with specific cognitive, sensory, or behavioral tasks. Although these biomarkers demonstrate substantial value, their effectiveness rely on patient cooperation and task design. Developing experimental paradigms that are more effective at eliciting specific EEG features or creating composite paradigms capable of simultaneously inducing multiple features may more effectively capture the brain activity characteristics of DOC patients, thereby supporting clinical applications. TMS-EEG is a technique for probing the neurodynamics within thalamocortical networks without involving sensory, motor, or cognitive functions. Parameters such as the perturbational complexity index (PCI) have been proposed as reliable indicators of consciousness, providing objective quantification of cortical dynamics. However, despite its high sensitivity and objectivity compared to traditional EEG methods, TMS-EEG is constrained by physiological artifacts, operational complexity, and variability in stimulation parameters and targets across individuals. Future research should aim to standardize experimental protocols, optimize stimulation parameters, and develop automated analysis techniques to improve the feasibility of TMS-EEG in clinical applications. Our analysis suggests that no single EEG biomarker currently achieves an ideal balance between accuracy, robustness, and generalizability. Progress is constrained by inconsistencies in analysis methods, parameter settings, and experimental conditions. Additionally, the heterogeneity of DOC etiologies and dynamic changes in brain function add to the complexity of assessment. Future research should focus on the standardization of EEG biomarker research, integrating features from resting-state, task-related, and TMS-EEG paradigms to construct multimodal diagnostic models that enhance evaluation efficiency and accuracy. Multimodal data integration (e.g., combining EEG with functional near-infrared spectroscopy) and advancements in source localization algorithms can further improve the spatial precision of biomarkers. Leveraging machine learning and artificial intelligence technologies to develop intelligent diagnostic tools will accelerate the clinical adoption of EEG biomarkers in DOC diagnosis and prognosis, allowing for more precise evaluations of consciousness states and personalized treatment strategies.

Biomolecular condensates are formed through phase separation of biomacromolecules such as proteins and RNAs. These condensates exhibit liquid-like properties that can futher transition into more stable material states. They form complex internal structures via multivalent weak interactions, enabling precise spatiotemporal regulations. However, the use of inconsistent and non-standardized terminology has become increasingly problematic, hindering academic exchange and the dissemination of scientific knowledge. Therefore, it is necessary to discuss the terminology related to biomolecular condensates in order to clarify concepts, promote interdisciplinary cooperation, enhance research efficiency, and support the healthy development of this field.

OBJECTIVE To analyze the potential adverse drug interactions （pADIs） of clarithromycin， and establish refined prescription pre-review rules. METHODS Outpatient prescriptions of clarithromycin in combination with other drugs were collected from January 1， 2024 to June 30， 2024 through hospital information system of the Third People’s Hospital of Bengbu. pADIs were identified and their risk severities were graded according to Lexicomp and Micromedex databases. Then， refined prescription pre- review rules for clarithromycin pADIs-related drugs were established according to the identification and risk level results. RESULTS Among 3 046 clarithromycin combined drug prescriptions， 946 cases of pADIs occurred in 812 prescriptions. There were 6， 415 and 525 cases classified as “contraindicated”，“ major” and “moderate”， respectively. The combination drugs with “contraindicated” levels were tamsulosin， rupatadine， domperidone and ticagrelor， while those with “major” levels were mainly theophylline， dexamethasone and amlodipine. Accordingly， 26 refined rules were established， including 4 items of “warning information→prescription interception”， 11 items of “warning information→prescription double signature” and 11 items of “attention information→prescription approval”. CONCLUSIONS There are “contraindicated” and “major” risks associated with clarithromycin and its combination drugs in the hospital， and refined prescription pre-review rules for clarithromycin combined drug prescription have been established successfully.

[Objective] To explore the therapeutic effects of intravenous immunoglobulin (IVIG) on dextran sodium sulfate (DSS)-induced ulcerative colitis (UC). [Methods] C57BL/6 mice were randomly assigned to the control group, the DSS group (model) and the DSS+IVIG group (treatment). The DSS group and the DSS+IVIG group received 3% DSS in drinking water to establish the acute UC mouse model. During the experiment, the DSS+IVIG group received IVIG (1 g/kg/2d) via tail vein injection, while the DSS group received equivalent saline via tail vein injection at the same dose and frequency. The symptoms of the mice were observed, body weight changes were recorded, and the disease activity index (DAI) was calculated daily. At the end of the experiment, hematoxylin-eosin (HE) staining was used to observe the pathological changes and inflammatory cell infiltration of colon tissue; Periodic acid-Schiff (PAS) staining was used to quantify the number of goblet cells; Luminex was used to detect the levels of inflammatory-related cytokines (such as TNF-α, IL-6 and MMPs) in colon; western blot and qRT-PCR were respectively used to detect the protein expression and mRNA levels of tight junction proteins (ZO-1, Occludin, Claudin-3). [Results] DSS induced weight loss, diarrhea, bloody stool, increased DAI score, and shortened colon length in mice. Compared with DSS group, after the administration of IVIG, the DAI score was significantly reduced (P<0.001), colon length was increased (P<0.001), infiltration of inflammatory cells and pathological damage were alleviated in colonic mucosa (P<0.001), the number of goblet cells were increased (P<0.05), and the levels of inflammatory-related cytokines TNF-α, IL-6, IL-6R, MMP2, MMP3 and Chitinase3like1 were decreased (all P<0.05). Western blot and qRT - PCR results showed that IVIG significantly up-regulated the protein expression of ZO-1, Occludin and claudin-3 (all P<0.05) and the mRNA levels of ZO-1 and Occludin (all P<0.05). [Conclusion] IVIG has protective effects on colitis by inhibiting the pathological release of inflammatory-related cytokines such as TNF-α, IL-6 and MMPs and restoring the integrity of intestinal barrier.

A 20-year-old male patient presented to the Department of Dermatology of Peking Union Medical College Hospital with complaints of an 8-year history of facial scarring, swelling of the lower limbs, and a 4-year history of scalp thickening. Physical examination showed thickening furrowing wrinkling of the skin on the face and behind the ears, ciliary body hirsutism, blepharoptosis, and cutis verticis gyrate. Both lower limbs were swollen, especially the knees and ankles. The skin of the palms and soles of the feet was keratinized and thickened. Laboratory examination using bone and joint X-ray showed periostosis of the proximal middle phalanges and metacarpals of both hands, distal ulna and radius, tibia and fibula, distal femurs, and metatarsals.Genetic testing revealed two variants in SLCO2A1, c.1658T > A and c.96+4A > C.Through multidisciplinary consultation, we confirmed the diagnosis of pachydermoperiostosis.

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.