Objective: To compare the predictive performance of the seasonal autoregressive integrated moving average (SARIMA) model, the Prophet model, and the Bayesian structural time series (BSTS) model in forecasting the incidence of hand, foot, and mouth disease (HFMD) , so as to provide a basis for optimizing the early warning system of this disease. Methods: Weekly incidence data of HFMD in Longgang District, Shenzhen City from 2014 to 2024 were collected. The HFMD incidence data from 2014-2019 and 2023 were used as the training set to construct SARIMA, Prophet, and BSTS models, while the data from 2024 were used as the test set to compare and evaluate the predictive performance of the three models. The technique for order preference by similarity to ideal solution (TOPSIS) method was employed to calculate the C-value. This approach integrates multiple evaluation metrics, such as the mean absolute error (MAE), mean squared error (MSE), root mean squared error (RMSE), and symmetric mean absolute percentage error (SMAPE), to comprehensively assess model performance. Results: A total of 150 111 cases of HFMD were reported in Longgang District from 2014 to 2024, with an average annual incidence of 400.72/105. The weekly incidence fluctuated between 0 and 63.78/105, exhibiting a bimodal seasonal pattern characterized by a primary peak from May to July and a secondary peak from September to October. In the training set, all three models demonstrated a good fit to the bimodal epidemic trend of HFMD, with the BSTS model achieving the best fit. The BSTS model yielded performance metrics as follows: MAE=0.124, MSE=0.050, RMSE=0.223, SMAPE=0.021, and a C-value of 1.000. In the test set, all three models, including SARIMA, Prophet, and BSTS, performed well for short-term predictions (≤16 weeks), with the Prophet model showing relatively superior predictive performance. However, the prediction accuracy of all models declined as the forecast horizon extended. During the primary peak period (May-July), the Prophet model exhibited better predictive performance, whereas the BSTS model performed relatively better during the secondary peak period (September-October). Conclusions For the short-term forecasting of weekly HFMD incidence, the Prophet model outperformed both the SARIMA and BSTS models. During the primary peak period, the Prophet model demonstrated superior predictive performance, whereas the BSTS model exhibited better accuracy in forecasting the secondary peak period.

Hygroscopicity research has long been a key focus and hot topic in Chinese materia medica（CMM）. Elucidating hygroscopic mechanisms plays a vital role in formulation design， process optimization， and storage condition selection. Hygroscopic models serve as essential tools for characterizing CMM hygroscopic mechanisms， with various types available. The double exponential model is a kinetic mathematical model constructed based on the law of conservation of energy and Fick's first law of diffusion， tailored to the physical properties of CMM extracts. In recent years， this model has been extensively applied to simulate the dynamic moisture absorption behavior of CMM extracts and solid dosage forms under varying humidity conditions. It has revealed the correlation between moisture absorption kinetic parameters and material properties， offering a new perspective for characterizing the moisture uptake behavior of CMM. This paper systematically reviews the application progress of this model in the field of CMM， analyzes its advantages， disadvantages， and challenges in this domain， and explores its potential application trends in other fields. It aims to provide references for elucidating the moisture absorption mechanisms of CMM and researching moisture-proofing technologies， while also offering insights for its broader application in food and polymer materials.

Periodontitis is a chronic inflammatory disease. The heterotopic colonization of periodontal pathogens results in the development of several systemic diseases. Porphyromonas gingivalis (P. gingivalis), a key pathogen for periodontitis, has been linked to the development of various cancers, such as oral squamous cell carcinoma (OSCC), lung cancer, esophageal cancer, pancreatic cancer, colorectal cancer, cervical cancer, and prostate cancer. P. gingivalis promote the progression of tumor through various mechanisms, P. gingivalis regulates proteins targeting cell cycle and apoptosis to promote proliferation of tumor cells directly, enhances tumor stemness by upregulating the expression of cluster of differentiation 44 (CD44) and cluster of differentiation 133 (CD133), activates inflammasome and p38/c-Jun N-terminal kinase 1(JNK) pathways, regulates tumor-associated neutrophil (TAN) polarization to remodel the tumor microenvironment, regulates epithelial-mesenchymal transition (EMT) to promote tumor metastasis, remodel macrophage function to evade host immune response, and regulates multi-communicating with symbiotic bacteria. In addition, P. gingivalis accelerates the progression of esophageal cancer, pancreatic cancer, colorectal cancer, and prostate cancer by promoting cell proliferation, inhibiting apoptosis, inducing chronic inflammation, and escaping immunity. However, the oral microbiome is a complex system, whether the interactions between oral bacteria affect tumor progression needs to be further investigated.

ObjectiveHistorically documented Zhejiang Atractylodis Macrocephalae Rhizoma（Baizhu） possesses premium characteristics such as phoenix-like head and crane-like neck， pronounced sweetness， and fragrant aroma. However， its current market circulation is low， and the processed products with Zhejiang-style characteristics are at the risk of being lost. This study aims to preserve the ancient Zhejiang-style processing techniques and evaluate them using modern scientific methods. MethodsMultidimensional intelligent sensory evaluation was used to digitally characterize the "quality-structure" of the external appearance of nine-steamed and nine-processed Baizhu medicinal materials（intermediate processed products） and the "odor-taste" of the internal quality of its decoction pieces（slices）， and the appearance parameters were digitally characterized by colorimeter， texture analyzer， electronic nose and electronic tongue， the chemical composition was analyzed via ultra-performance liquid chromatography-quadrupole-time-of-flight mass spectrometry（UPLC-Q-TOF-MS/MS）. Then， cluster analysis on the differences in odor between the medicinal materials（intermediate processed products） and decoction pieces（slices） of nine-steamed and nine-processed Baizhu was conducted， as well as the differences in taste between water-soluble and alcohol-soluble extracts of the decoction pieces（slices）， and the correlation analysis of chroma value-alcohol-soluble extract content-component response value. ResultsThe nine-steamed and nine-processed Baizhu had a dark brown to black epidermis， a brownish-yellow to brownish-gray cross-section， a slightly tough texture， a faint odor， and a slightly sweet， bitter and pungent taste. Texture analyzer measurements revealed minimal adhesion and maximum recovery in the middle section of the characteristic processed Baizhu， consistent with the processing endpoint of thorough steaming and cooking. The head section showed the highest internal hardness， elasticity and chewiness， indicating a denser texture in this area. The electronic nose sensor could clearly distinguish the difference between the medicinal materials and its decoction pieces， with a more significant clustering effect at 60 ℃ for 30 minutes compared to ambient temperature headspace for 2 hours， highlighting the significant impact of the baking degree before slicing on the quality. The electronic tongue taste signal map clearly distinguished the differences between water-soluble and alcohol-soluble extracts of nine-steamed and nine-processed Baizhu decoction pieces， and the addition of auxiliary materials during processing could enhance its alcohol-soluble extract content. A total of 82 chemical components were identified in the characteristic processed Baizhu. After processing， the contents of 58 components increased， while 24 components decreased. Correlation analysis revealed significant negative correlations（P<0.01） between ethanol-soluble extract content and colorimetric values of brightness（L^*）， yellow-bule value（b^*）， and total color difference（E^*_ab）. E^*_ab showed marked negative correlations（P<0.05） with the response values of isochlorogenic acid A and C. ConclusionThis study establishes a modern intelligent sensory evaluation model for multidimensional holographic characterization of nine-steamed and nine-processed Baizhu， clarifying the correlation between increased isochlorogenic acid content and the visual color appearance after different steaming cycles， as well as its intrinsic alcohol-soluble extracts. This provides a reference for quality evaluation and processing standards of the Zhejiang-style characteristic processed products.

This article presents a case study of a patient who visited the Geriatric Department of Peking Union Medical College Hospital due to "palpitations, shortness of breath for more than 2 years, limb weakness for 6 months, edema, and nocturnal dyspnea for 2 months". The patient exhibited decreased muscle strength in the limbs and involvement of swallowing and respiratory muscles, alongside complications of heart failure and various arrhythmias which were predominantly atrial. Laboratory tests revealed the presence of multiple autoantibodies and notably anti-mitochondrial antibodies. Following a comprehensive multidisciplinary evaluation, the patient was diagnosed with anti-mitochondrial antibody-associated inflammatory myopathy. Treatment involved a combination of glucocorticoids and immunosuppressants, along with resistance exercises for muscle strength and rehabilitation training for lung function, resulting in significant improvement of clinical symptoms. The case underscores the importance of collaborative multidisciplinary approaches in diagnosing and treating rare diseases in elderly patients, where careful consideration of clinical manifestations and subtle abnormal clinical data can lead to effective interventions.

Objective To explore the diagnostic value of exhaled volatile organic compounds (VOCs) for cystic fibrosis (CF). Methods A systematic search was conducted in PubMed, EMbase, Web of Science, Cochrane Library, CNKI, Wanfang, VIP, and SinoMed databases up to August 7, 2024. Studies that met the inclusion criteria were selected for data extraction and quality assessment. The quality of included studies was assessed by the Newcastle-Ottawa Scale (NOS), and the risk of bias and applicability of included prediction model studies were assessed by the prediction model risk of bias assessment tool (PROBAST). Results A total of 10 studies were included, among which 5 studies only identified specific exhaled VOCs in CF patients, and another 5 developed 7 CF risk prediction models based on the identification of VOCs in CF. The included studies reported a total of 75 exhaled VOCs, most of which belonged to the categories of acylcarnitines, aldehydes, acids, and esters. Most models (n=6, 85.7%) only included exhaled VOCs as predictive factors, and only one model included factors other than VOCs, including forced expiratory flow at 75% of forced vital capacity (FEF75) and modified Medical Research Council scale for the assessment of dyspnea (mMRC). The accuracy of the models ranged from 77% to 100%, and the area under the receiver operating characteristic curve ranged from 0.771 to 0.988. None of the included studies provided information on the calibration of the models. The results of the Prediction Model Risk of Bias Assessment Tool (PROBAST) showed that the overall bias risk of all predictive model studies was high, and the overall applicability was unclear. Conclusion The exhaled VOCs reported in the included studies showed significant heterogeneity, and more research is needed to explore specific compounds for CF. In addition, risk prediction models based on exhaled VOCs have certain value in the diagnosis of CF, but the overall bias risk is relatively high and needs further optimization from aspects such as model construction and validation.

Thyroid diseases are common clinical endocrine disorders， and their pathogenesis is generally considered to be closely related to genetic predisposition factors， immune system disorders， hormone levels， etc. Xiaoyaosan is widely used in the treatment of various thyroid diseases with excellent effects. This study summarized the relevant literature on the treatment of thyroid diseases with modified Xiaoyaosan prescriptions and their active ingredients from aspects such as theoretical analysis， clinical research， and mechanism research. Theoretical analysis revealed that Xiaoyaosan could not only disperse stagnated liver qi but also replenish deficient spleen Qi， which was consistent with the etiology and pathogenesis of thyroid diseases. Clinical studies found that Xiaoyaosan and its modified prescriptions could be widely used in the treatment of multiple thyroid diseases， such as hyperthyroidism， Hashimoto's thyroiditis， and thyroid nodules. Both the use of modified Xiaoyaosan alone and in combination with medications such as methimazole， propylthiouracil， and euthyrox could effectively improve patients' clinical symptoms. In the mechanism research， this study discovered that the whole formula of Xiaoyaosan and its modified prescriptions could inhibit inflammatory reactions， regulate immune balance， and delay liver damage during the treatment of thyroid diseases. The research on Xiaoyaosan for treating thyroid diseases mainly focused on thyroid cancer， autoimmune thyroiditis， hyperthyroidism， and hypothyroidism. The mechanisms of action mainly involved promoting cell apoptosis， inhibiting cell proliferation and migration， arresting the cell cycle， and regulating thyroid hormone levels. In conclusion， this study systematically combs and summarizes the research status of Xiaoyaosan in treating thyroid diseases through literature retrieval， aiming to provide new perspectives and new ideas for the prevention and treatment of thyroid diseases with traditional Chinese medicine.

Objective To prepare a thermosensitive hydrogel scaffold loaded with bone marrow mesenchymal stem cells（BMSCs） and resveratrol liposomes （RSV-LIP） to form a therapeutic unit and evaluate its treatment efficacy for traumatic brain injury （TBI）. Methods BMSCs were extracted from rats, and RSV-LIP was prepared and characterized. Cell models were constructed to investigate the pharmacological effects of BMSCs combined with RSV-LIP. BMSCs and RSV-LIP were then loaded into the hydrogel, and a TBI mouse model was established to evaluate the therapeutic effects of the hydrogel. Results The RSV-LIP had a particle size of 127.8 nm, a Zeta potential of −4.9 mV, an encapsulation efficiency of 78.50%, and a drug loading content of 2.37%. Live-dead staining indicated good biocompatibility of the hydrogel. The combination of BMSCs and RSV-LIP significantly inhibited TNF-α and reduced ROS levels, promoting cell migration in scratch assays. Compared to the control group, the hydrogel group showed significantly lower mNSS scores （P<0.01）, higher hanging scores （P<0.001）, and reduced stepping errors （P<0.001）. Conclusion The combination of BMSCs and RSV-LIP exhibited antioxidative stress, anti-inflammatory, and neurogenic cell migration-promoting effects. When loaded into a hydrogel scaffold and locally implanted, it could improve the motor and sensory functions in TBI mice.

Oral squamous cell carcinoma (OSCC), the most common type of head and neck malignancy, has a poor prognosis owing to its high invasiveness and high rate of cervical lymph node metastasis. The tumor microenvironment (TME) is a complex microenvironment that is essential for tumor cell survival. Tumor-associated immune cell (TAIC), the main stromal cell of TME, regulates the proliferation, invasion, epithelial-mesenchymal transformation (EMT), and anti-tumor immunity of OSCC. M2-tumor-associated macrophages (TAMs) promote the invasion and metastasis of OSCC through the macrophage migration inhibitory factor/NOD-like receptor family pyrin domain containing 3/interleukin (IL)-1β axis, while N2-tumor-associated neutrophils (TANs) regulate the proliferation and EMT of OSCC through the Janus kinase 2/signal transducer and activator of transcription 3 pathway. Meanwhile, myeloid-derived suppressor cells (MDSCs) accelerate the progression of OSCC by secreting IL-6, IL-10, and transforming growth factor (TGF)-β; T cells promote inflammation by secreting IL-17 and inhibit inflammation-mediated tumor immune response by secreting IL-10 and TGF-β; and natural killer (NK) cells recognize and attack OSCC cells to inhibit OSCC progression. TAIC interaction network also regulates OSCC progression. M2-TAMs regulate the invasion and metastasis of OSCC by promoting T cell apoptosis through the secretion of IL-10 and programmed death-ligand (PD-L) -1, while N2-TANs inhibit T cell proliferation and cytotoxicity by secreting LOX-1 and arginase-1. MDSCs inhibit the proliferation and anti-tumor effects of CD8+ T cells through the inactivation of programmed cell death (PD)-1/PD-L1 signaling. Additionally, MDSCs inhibit the proliferation of T cells by decreasing the expression of the CD3-zeta chain and interferon-γ (IFN-γ). Moreover, tumor-infiltrating lymphocytes and NK cells were found to be positively correlated in OSCC progression. Therefore, target regulation, related signaling pathways, and the interaction network of TAIC may serve as promising therapeutic targets in the immunotherapy of OSCC. In this review, we summarize the recent research on the effects of TAIC and their interaction network in the TME in the progression of OSCC and explore its application in the early diagnosis and treatment of OSCC

[Objective] To conduct serological identification and molecular mechanism study on a ambiguous ABO blood group. [Methods] Standard serological techniques were used for the forward and reverse typing of ABO blood type. ABO gene coding and regulatory regions were analyzed by PCR after DNA extraction. Monoclonal sequencing was used to detect the haplotypes of the DNA sequence, and bioinformatics analysis was applied to predict the possible translation outcomes of the mutated DNA sequence. [Results] The sample’s red blood cells showed mixed field agglutination with anti-A, and the serum agglutinated with B cells, exhibiting serological characteristics of subtype A. Direct sequencing and monoclonal sequencing analysis of the ABO gene confirmed one allele as O02, the other had a c.27delC mutation compared with A102, which could cause the translation sequence to terminate prematurely at the 19th amino acids. Analysis and prediction suggested that the mutation might affect the function of the transferase through mechanisms such as shifting the initiation codon, altering the reading frame and affecting the splice sites. [Conclusion] This case is a rare A subtype caused by the c.27delC variation, and the impact on the glycosyltransferase may involve multiple mechanisms, which require further research and exploration.