Currently, the drug delivery system (DDS) based on nanomaterials has become a hot interdisciplinary research topic. One of the core issues is drug loading and controlled release, in which the key lever is carriers. Vaterite, as an inorganic porous nano-material, is one metastable structure of calcium carbonate, full of micro or nano porous. Recently, vaterite has attracted more and more attention, due to its significant advantages, such as rich resources, easy preparations, low cost, simple loading procedures, good biocompatibility and many other good points. Vaterite, gained from suitable preparation strategies, can not only possess the good drug carrying performance, like high loading capacity and stable loading efficiency, but also improve the drug release ability, showing the better drug delivery effects, such as targeting release, pH sensitive release, photothermal controlled release, magnetic assistant release, optothermal controlled release. At the same time, the vaterite carriers, with good safety itself, can protect proteins, enzymes, or other drugs from degradation or inactivation, help imaging or visualization with loading fluorescent drugs in vitro and in vivo, and play synergistic effects with other therapy approaches, like photodynamic therapy, sonodynamic therapy, and thermochemotherapy. Latterly, some renewed reports in drug loading and controlled release have led to their widespread applications in diverse fields, from cell level to clinical studies. This review introduces the basic characteristics of vaterite and briefly summarizes its research history, followed by synthesis strategies. We subsequently highlight recent developments in drug loading and controlled release, with an emphasis on the advantages, quantity capacity, and comparations. Furthermore, new opportunities for using vaterite in cell level and animal level are detailed. Finally, the possible problems and development trends are discussed.

Intraoperative cell salvage (IOCS) has been widely applied as an important blood conservation measure in surgical operations. However, there is currently a lack of clinical practice guidelines for the implementation of IOCS in patients with malignant tumors. This report aims to provide clinicians with recommendations on the use of IOCS in patients with malignant tumors based on the review and assessment of the existed evidence. Data were derived from databases such as PubMed, Embase, the Cochrane Library and Wanfang. The guideline development team formulated recommendations based on the quality of evidence, balance of benefits and harms, patient preferences, and health economic assessments. This study constructed seven major clinical questions. The main conclusions of this guideline are as follows: 1) Compared with no perioperative allogeneic blood transfusion (NPABT), perioperative allogeneic blood transfusion (PABT) leads to a more unfavorable prognosis in cancer patients (Recommended); 2) Compared with the transfusion of allogeneic blood or no transfusion, IOCS does not lead to a more unfavorable prognosis in cancer patients (Recommended); 3) The implementation of IOCS in cancer patients is economically feasible (Recommended); 4) Leukocyte depletion filters (LDF) should be used when implementing IOCS in cancer patients (Strongly Recommended); 5) Irradiation treatment of autologous blood to be reinfused can be used when implementing IOCS in cancer patients (Recommended); 6) A careful assessment of the condition of cancer patients (meeting indications and excluding contraindications) should be conducted before implementing IOCS (Strongly Recommended); 7) Informed consent from cancer patients should be obtained when implementing IOCS, with a thorough pre-assessment of the patient's condition and the likelihood of blood loss, adherence to standardized internally audited management procedures, meeting corresponding conditions, and obtaining corresponding qualifications (Recommended). In brief, current evidence indicates that IOCS can be implemented for some malignant tumor patients who need allogeneic blood transfusion after physician full evaluation, and LDF or irradiation should be used during the implementation process.

Objective: To identify the spatio-temporal clustering analysis of mumps in Wenzhou City, Zhejiang Province from 2010 to 2023, so as to provide the basis for improving mumps prevention and control strategies. Methods: Data of mumps cases in Wenzhou City from 2010 to 2023 were collected from the Monitoring and Reporting Management System of Chinese Disease Prevention and Control Information System. The spatio-temporal clustering characteristics of mumps incidence were identified using spatial autocorrelation analysis and spatio-temporal scan analysis. Results: A total of 20 455 mumps cases were reported in Wenzhou City from 2010 to 2023, with an average annual incidence of 17.54/105. There were 12 919 male and 7 536 female cases, with a male-to-female ratio of 1.71∶1. The children aged 5-<10 years had the highest incidence of mumps at 135.29/105. The incidence of mumps showed a downward trend from 46.82/105 in 2010 to 3.59/105 in 2023 (P<0.05). The incidence of mumps peaked from May to July and from November to January during 2010 and 2012, the winter peak became less evident after 2013, and no seasonal trends were observed after 2020. Spatial autocorrelation analysis showed there was a positive spatial correlation of mumps of other years, with the exception of 2018 (all Moran's I >0, all P<0.05). Lucheng District, Longwan District, Ouhai District, Cangnan County and Rui'an City were high-high clustering sites. Spatio-temporal scan analysis showed that the primary clustering area was centered in Nanbaixiang Street, Ouhai District, covering 50 towns (streets), with the clustering time from April 2010 to August 2013; the secondary clustering area was centered in Zaoxi Town, Cangnan County, covering 24 towns (streets), with the clustering time from January 2010 to June 2013. Conclusions The incidence of mumps in Wenzhou City from 2010 to 2023 showed a downward trend. The urban areas, Cangnan County and Rui'an City were the clustering areas.

ObjectiveTo explore the clinical safety of Feilike Mixture （FLK） in the real world. MethodsThe safety of all children who received FLK from 29 institutions in 12 provinces between January 21，2021 and December 25，2021 was evaluated through prospective centralized surveillance and a nested case control study. ResultsA total of 3 035 juveniles were included. There were 29 research centers involved，which are distributed across 12 provinces，including one traditional Chinese medicine （TCM） hospital and 28 general hospitals. The average age among the juveniles was （4.77±3.56） years old，and the average weight was （21.81±12.97） kg. Among them，119 cases （3.92%） of juveniles had a history of allergies. Acute bronchitis was the main diagnosis for juveniles，with 1 656 cases （54.46%）. FLK was first used in 2 016 cases （66.43%），and 142 juvenile patients had special dosages，accounting for 4.68%. Among them，92 adverse drug reactions （ADRs） occurred，including 73 cases of gastrointestinal system disorders，10 cases of metabolic and nutritional disorders，eight cases of skin and subcutaneous tissue diseases，two cases of vascular and lymphatic disorders，and one case of systemic diseases and various reactions at the administration site. The manifestations of ADRs were mainly diarrhea，stool discoloration，and vomiting，and no serious ADRs occurred. The results of multi-factor analysis indicated that special dosages （the use of FLK）［odds ratio （OR） of 2.642， 95% confidence interval （CI） of 1.105-6.323］，combined administration： spleen aminopeptide （OR of 4.978， 95%CI of 1.200-20.655），and reason for combined administration： anti-infection （OR of 1.814， 95%CI of 1.071-3.075） were the risk factors for ADRs caused by FLK. Conclusion92 ADRs occurred among 3 035 juveniles using FLK. The incidence of ADRs caused by FLK was 3.03%，and the severity was mainly mild or moderate. Generally，the prognosis was favorable after symptomatic treatment such as drug withdrawal or dosage reduction，suggesting that FLK has good clinical safety.

ObjectiveTo analyze the characteristic expression patterns of six neurotransmitters including 5-hydroxytryptamine （5-HT）， dopamine （DA）， acetylcholine （ACh）， norepinephrine （NE）， inhibitory neurotransmitter （INH）， and excitatory neurotransmitter （EXC） in the whole brain and different brain regions of depression patients by Search of Encephalo Telex （SET）， providing new ideas for the study of heterogeneous etiology of depression. Methods（1） A retrospective study was conducted on supra-slow signals of EEG fluctuations in 1 028 patients with depression. The SET system was used to obtain the expression information of six neurotransmitters in the whole brain and 12 brain regions： left frontal region （F3）， right frontal region （F4）， left central region （C3）， right central region （C4）， left parietal region （P3）， right parietal region （P4）， left occipital region （O1）， right occipital region （O2）， left anterior temporal region （F7）， right anterior temporal region （F8）， left posterior temporal region （T5）， and right posterior temporal region （T6）. The expression information of each neurotransmitter was compared with the normal model， and it was found that single neurotransmitter was in one of three states： increased， decreased， or normal expression. The simultaneous expression states of six neurotransmitters in the brain space were referred to as the expression pattern of multiple neurotransmitters. （2） A MySQL database was established to analyze the actual expression patterns of different neurotransmitters in the whole brain of patients with depression. （3） Factor analysis was conducted to further analyze the characteristic rules of 78 variables of neurotransmitters in the whole brain and 12 brain regions in depression patients. Results（1） The expression of single neurotransmitters in the whole brain and different brain regions of the total depression population showed one of three expression states （increased/decreased/normal）， being normal in the majority. The decreased and increased expression of 5-HT， ACh， DA， INH， EXC， and NE in the whole brain occurred in 6% and 25%， 31% and 17%， 36% and 9%， 15% and 31%， 32% and 14%， and 22% and 22%， respectively. （2） The antagonizing pairs of neurotransmitters （EXC/INH， DA/5-HT， and ACh/NE） showed significant antagonistic relationships in the whole brain and different brain regions， with a strong negative correlation between EXC and INH （P<0.01， |r| values ranging from 0.69 to 0.76）， a strong negative correlation between DA and 5-HT （P<0.01， |r| values ranging from 0.83 to 0.90）， and a moderate negative correlation between ACh and NE （P<0.01， with |r| values ranging from 0.56 to 0.66）. Meanwhile， non-antagonizing pairs of neurotransmitters in the whole brain and different brain regions also showed correlations， with DA/NE （P<0.01， |r| values ranging from 0.38 to 0.46） and NE/EXC （P<0.01， |r| values ranging from 0.56 to 0.61） showing weak and moderate negative correlations， respectively， and DA/EXC showing a weak positive correlation （P<0.01， |r| values ranging from 0.38 to 0.47）. （3） The six neurotransmitters in the 1 028 patients with depression presented a total of 170 expression patterns in the whole brain. The top 30 expression patterns were reported in this paper， with a cumulative rate of 60.60%， including patterns ① INH+/5-HT-/ACh+/DA+/NE-/EXC- （9.05%）， ② INH+/5-HT-/ACh↓/DA+/NE-/EXC- （4.57%）， and ③ INH+/5-HT-/ACh+/DA+/NE↓/EXC- （3.31%）. That is， the proportion of depression patients with normal levels of all the six neurotransmitters was 9.05%， and the patients with at least one neurotransmitter abnormality accounted for 91.95%. （4） The factor analysis extracted 22 common factors from 78 variables in the whole brain and different brain regions. These common factors showed the absolute values of loadings ranging from 0.32 to 0.86 and the eigenvalues （F） ranging from 1.03 to 13.43， with a cumulative contribution rate of 76.82%. The characteristic expression patterns included ① ACh_P3↓/ACh_W↓/ACh_C3↓/ACh_F3↓/ACh_O1↓/ACh_T5↓/ACh_F7↓/NE_P3↑/NE_W↑/NE_C3↑/NE_F3↑/NE_O1↑/NE_T5↑/NE_F7↑ （F=13.43， whole brain）， ② 5-HT_O2↑/DA_O2↓/5-HT_P4↑/DA_P4↓/5-HT_W↑/DA_W↓/5-HT_C4↑/DA_C4↓ （F=5.94）， and ③ EXC_F4↓/DA_F4↓/NE_F4↑/INH_F4↑/5-HT_F4↑/ACh_F4↓ （F=5.33）. ConclusionThe actual 170 expression patterns of 6 neurotransmitters in the whole brain of 1 028 depression patients indicate that depression is a heterogeneous disease with individualized characteristics. The 22 characteristic expression patterns in the whole brain and 12 brain regions verify the pathogenesis hypothesis of multi-neurotransmitters oscillation imbalance in brains of depression patients. In summary， this study provides new guidance for the etiology， diagnosis， and treatment of depression and establishes a methodological foundation for the effectiveness evaluation of individualized treatment of depression by traditional Chinese medicine based on the objective biological markers.

ObjectiveTo analyze the characteristic expression patterns of six neurotransmitters including 5-hydroxytryptamine （5-HT）， dopamine （DA）， acetylcholine （ACh）， norepinephrine （NE）， inhibitory neurotransmitter （INH）， and excitatory neurotransmitter （EXC） in the whole brain and different brain regions of depression patients by Search of Encephalo Telex （SET）， providing new ideas for the study of heterogeneous etiology of depression. Methods（1） A retrospective study was conducted on supra-slow signals of EEG fluctuations in 1 028 patients with depression. The SET system was used to obtain the expression information of six neurotransmitters in the whole brain and 12 brain regions： left frontal region （F3）， right frontal region （F4）， left central region （C3）， right central region （C4）， left parietal region （P3）， right parietal region （P4）， left occipital region （O1）， right occipital region （O2）， left anterior temporal region （F7）， right anterior temporal region （F8）， left posterior temporal region （T5）， and right posterior temporal region （T6）. The expression information of each neurotransmitter was compared with the normal model， and it was found that single neurotransmitter was in one of three states： increased， decreased， or normal expression. The simultaneous expression states of six neurotransmitters in the brain space were referred to as the expression pattern of multiple neurotransmitters. （2） A MySQL database was established to analyze the actual expression patterns of different neurotransmitters in the whole brain of patients with depression. （3） Factor analysis was conducted to further analyze the characteristic rules of 78 variables of neurotransmitters in the whole brain and 12 brain regions in depression patients. Results（1） The expression of single neurotransmitters in the whole brain and different brain regions of the total depression population showed one of three expression states （increased/decreased/normal）， being normal in the majority. The decreased and increased expression of 5-HT， ACh， DA， INH， EXC， and NE in the whole brain occurred in 6% and 25%， 31% and 17%， 36% and 9%， 15% and 31%， 32% and 14%， and 22% and 22%， respectively. （2） The antagonizing pairs of neurotransmitters （EXC/INH， DA/5-HT， and ACh/NE） showed significant antagonistic relationships in the whole brain and different brain regions， with a strong negative correlation between EXC and INH （P<0.01， |r| values ranging from 0.69 to 0.76）， a strong negative correlation between DA and 5-HT （P<0.01， |r| values ranging from 0.83 to 0.90）， and a moderate negative correlation between ACh and NE （P<0.01， with |r| values ranging from 0.56 to 0.66）. Meanwhile， non-antagonizing pairs of neurotransmitters in the whole brain and different brain regions also showed correlations， with DA/NE （P<0.01， |r| values ranging from 0.38 to 0.46） and NE/EXC （P<0.01， |r| values ranging from 0.56 to 0.61） showing weak and moderate negative correlations， respectively， and DA/EXC showing a weak positive correlation （P<0.01， |r| values ranging from 0.38 to 0.47）. （3） The six neurotransmitters in the 1 028 patients with depression presented a total of 170 expression patterns in the whole brain. The top 30 expression patterns were reported in this paper， with a cumulative rate of 60.60%， including patterns ① INH+/5-HT-/ACh+/DA+/NE-/EXC- （9.05%）， ② INH+/5-HT-/ACh↓/DA+/NE-/EXC- （4.57%）， and ③ INH+/5-HT-/ACh+/DA+/NE↓/EXC- （3.31%）. That is， the proportion of depression patients with normal levels of all the six neurotransmitters was 9.05%， and the patients with at least one neurotransmitter abnormality accounted for 91.95%. （4） The factor analysis extracted 22 common factors from 78 variables in the whole brain and different brain regions. These common factors showed the absolute values of loadings ranging from 0.32 to 0.86 and the eigenvalues （F） ranging from 1.03 to 13.43， with a cumulative contribution rate of 76.82%. The characteristic expression patterns included ① ACh_P3↓/ACh_W↓/ACh_C3↓/ACh_F3↓/ACh_O1↓/ACh_T5↓/ACh_F7↓/NE_P3↑/NE_W↑/NE_C3↑/NE_F3↑/NE_O1↑/NE_T5↑/NE_F7↑ （F=13.43， whole brain）， ② 5-HT_O2↑/DA_O2↓/5-HT_P4↑/DA_P4↓/5-HT_W↑/DA_W↓/5-HT_C4↑/DA_C4↓ （F=5.94）， and ③ EXC_F4↓/DA_F4↓/NE_F4↑/INH_F4↑/5-HT_F4↑/ACh_F4↓ （F=5.33）. ConclusionThe actual 170 expression patterns of 6 neurotransmitters in the whole brain of 1 028 depression patients indicate that depression is a heterogeneous disease with individualized characteristics. The 22 characteristic expression patterns in the whole brain and 12 brain regions verify the pathogenesis hypothesis of multi-neurotransmitters oscillation imbalance in brains of depression patients. In summary， this study provides new guidance for the etiology， diagnosis， and treatment of depression and establishes a methodological foundation for the effectiveness evaluation of individualized treatment of depression by traditional Chinese medicine based on the objective biological markers.

Objective: Machine learning (ML) has been reported to have better predictive capability than traditional statistical techniques. The aim of this study was to assess the efficacy of ML algorithms and logistic regression (LR) for predicting depressive symptoms during the COVID-19 pandemic. Methods: Analyses were carried out in a national cross-sectional study involving 21,916 participants. The ML algorithms in this study included random forest (RF), support vector machine (SVM), neural network (NN), and gradient boosting machine (GBM) methods. The performance indices were sensitivity, specificity, accuracy, precision, F1-score, and area under the receiver operating characteristic curve (AUC). Results: LR and NN had the best performance in terms of AUCs. The risk of overfitting was found to be negligible for most ML models except for RF, and GBM obtained the highest sensitivity, specificity, accuracy, precision, and F1-score. Therefore, LR, NN, and GBM models ranked among the best models. Conclusion Compared with ML models, LR model performed comparably to ML models in predicting depressive symptoms and identifying potential risk factors while also exhibiting a lower risk of overfitting.

Purpose: The aim of this study was to investigate the feasibility of an intelligent handheld ultrasound (US) device for assisting non-expert general practitioners (GPs) in detecting carotid plaques (CPs) in community populations. Methods: This prospective parallel controlled trial recruited 111 consecutive community residents. All of them underwent examinations by non-expert GPs and specialist doctors using handheld US devices (setting A, setting B, and setting C). The results of setting C with specialist doctors were considered the gold standard. Carotid intima-media thickness (CIMT) and the features of CPs were measured and recorded. The diagnostic performance of GPs in distinguishing CPs was evaluated using a receiver operating characteristic curve. Inter-observer agreement was compared using the intragroup correlation coefficient (ICC). Questionnaires were completed to evaluate clinical benefits. Results: Among the 111 community residents, 80, 96, and 112 CPs were detected in settings A, B, and C, respectively. Setting B exhibited better diagnostic performance than setting A for detecting CPs (area under the curve, 0.856 vs. 0.749; P<0.01). Setting B had better consistency with setting C than setting A in CIMT measurement and the assessment of CPs (ICC, 0.731 to 0.923). Moreover, measurements in setting B required less time than the other two settings (44.59 seconds vs. 108.87 seconds vs. 126.13 seconds, both P<0.01). Conclusion Using an intelligent handheld US device, GPs can perform CP screening and achieve a diagnostic capability comparable to that of specialist doctors.

Background: s/Aims: Sarcomatoid hepatocellular carcinoma (HCC) is a rare histological subtype of HCC characterized by extremely poor prognosis; however, its molecular characterization has not been elucidated. Methods: In this study, we conducted an integrated multiomics study of whole-exome sequencing, RNA-seq, spatial transcriptome, and immunohistochemical analyses of 28 paired sarcomatoid tumor components and conventional HCC components from 10 patients with sarcomatoid HCC, in order to identify frequently altered genes, infer the tumor subclonal architectures, track the genomic evolution, and delineate the transcriptional characteristics of sarcomatoid HCCs. Results: Our results showed that the sarcomatoid HCCs had poor prognosis. The sarcomatoid tumor components and the conventional HCC components were derived from common ancestors, mostly accessing similar mutational processes. Clonal phylogenies demonstrated branched tumor evolution during sarcomatoid HCC development and progression. TP53 mutation commonly occurred at tumor initiation, whereas ARID2 mutation often occurred later. Transcriptome analyses revealed the epithelial–mesenchymal transition (EMT) and hypoxic phenotype in sarcomatoid tumor components, which were confirmed by immunohistochemical staining. Moreover, we identified ARID2 mutations in 70% (7/10) of patients with sarcomatoid HCC but only 1–5% of patients with non-sarcomatoid HCC. Biofunctional investigations revealed that inactivating mutation of ARID2 contributes to HCC growth and metastasis and induces EMT in a hypoxic microenvironment. Conclusions We offer a comprehensive description of the molecular basis for sarcomatoid HCC, and identify genomic alteration (ARID2 mutation) together with the tumor microenvironment (hypoxic microenvironment), that may contribute to the formation of the sarcomatoid tumor component through EMT, leading to sarcomatoid HCC development and progression.

Objective: Machine learning (ML) has been reported to have better predictive capability than traditional statistical techniques. The aim of this study was to assess the efficacy of ML algorithms and logistic regression (LR) for predicting depressive symptoms during the COVID-19 pandemic. Methods: Analyses were carried out in a national cross-sectional study involving 21,916 participants. The ML algorithms in this study included random forest (RF), support vector machine (SVM), neural network (NN), and gradient boosting machine (GBM) methods. The performance indices were sensitivity, specificity, accuracy, precision, F1-score, and area under the receiver operating characteristic curve (AUC). Results: LR and NN had the best performance in terms of AUCs. The risk of overfitting was found to be negligible for most ML models except for RF, and GBM obtained the highest sensitivity, specificity, accuracy, precision, and F1-score. Therefore, LR, NN, and GBM models ranked among the best models. Conclusion Compared with ML models, LR model performed comparably to ML models in predicting depressive symptoms and identifying potential risk factors while also exhibiting a lower risk of overfitting.