ObjectiveTo provide a reference for the rational clinical use of cold Chinese medicines by sorting and analyzing their properties， flavors， meridian tropism， primary therapeutic indications， methods of administration， dosages， and precautions as recorded in the 2020 edition of Pharmacopoeia of the People's Republic of China （Chinese Pharmacopoeia）. MethodsCold Chinese medicines for internal and external use included in the 2020 edition of Chinese Pharmacopoeia were entered one by one， and their efficacy， properties， flavors， meridian tropism， methods of administration， dosages， and usage precautions were statistically classified and summarized to guide clinical medication use. ResultsA total of 259 cold Chinese medicines for internal use were included and categorized into 18 efficacy groups， mainly comprising heat-clearing drugs， water-excreting and dampness-draining drugs， and phlegm-resolving， cough- and asthma-relieving drugs. Their predominant flavors were bitter， sweet， and pungent， and they primarily entered the liver， lung， and stomach meridians. The main methods of administration included decocting first， grinding into powder for oral use， or preparing into pills or powders， with most dosages ranging from 9 to 15 g. A total of 83 cold Chinese medicines for external use were included， involving 16 efficacy categories. Their main flavors were bitter， sweet， and pungent， primarily entering the liver， lung， and large intestine meridians. The main external application methods were grinding into powder for topical use or preparing decoctions for fumigation and washing， with most dosages ranging from 9 to 15 g. Whether for internal or external use， cold Chinese medicines should be used with caution or contraindicated in pregnant women. ConclusionThe cold Chinese medicines included in the 2020 edition of the Chinese Pharmacopoeia are mainly suitable for patients with carbuncles， swellings， and coughs. However， in clinical practice， it is necessary to strictly follow the principles of syndrome differentiation and treatment， pay attention to administration methods and dosages， and use cold medicines rationally and effectively to improve clinical efficacy.

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.

ObjectiveTo explore the mechanism of Jiebiao Qingli decoction （JQD） in treating pneumonia caused by influenza A virus （IAV） infection. MethodsA total of 132 Balb/c mice were randomly assigned into normal control （NC）， model control （IAV）， oseltamivir （OSV， 37.5 mg·kg^-1）， and high-， medium-， low-dose JQD （H-， M-， and L-JQD： 6.05， 3.02， and 1.51 g·kg^-1， respectively） groups. The NC group was treated with normal saline nasal drops， and the other groups were intranasally inoculated with A/Brisbane/02/2018 （H1N1） ［pdm09-like virus （H1N1）］ for the modeling of IAV infection. Two hours post-modeling， the NC and IAV groups were administrated with normal saline by gavage， while other groups received corresponding drugs for 7 d. The body mass， survival status， and deaths of mice were recorded daily during the administration of the drugs. On days 3 and 7， the lung index was measured for mice in each group. Pathological changes in the lung tissue were observed via hematoxylin-eosin staining. Real-time fluorescence quantitative polymerase chain reaction （Real-time PCR） was conducted to measure the viral load （IAV-M） and the mRNA levels of Toll-like receptor 7 （TLR7）， p38 mitogen-activated protein kinase （p38 MAPK）， and nuclear factor-kappa B （NF-κB） in the lung tissue. Western blot was employed to measure the protein levels of p38 MAPK and NF-κB. Enzyme-linked immunosorbent assay was used to quantify serum levels of interleukin-2 （IL-2）， interleukin-6 （IL-6）， and tumor necrosis factor-alpha （TNF-α）. ResultsCompared with the NC group， the IAV group showed reduced survival quality and survival days （P<0.01）， lung congestion， inflammatory cell infiltration， elevated lung index （P<0.01）， increased viral load （P<0.01）， upregulated TLR7， p38 MAPK， and NF-κB levels （P<0.05， P<0.01）， decreased IL-2 level （P<0.01）， and elevated IL-6 and TNF-α levels （P<0.01）. Compared with the IAV group， H-JQD prolonged survival days （P<0.05）. All JQD groups alleviated pathological changes in the lung tissue and reduced the lung index （P<0.01）. M-JQD and H-JQD decreased the viral load （P<0.01）. H-JQD downregulated the mRNA levels of TLR7， p38 MAPK， and NF-κB （P<0.05， P<0.01） and the protein levels of p38 MAPK and NF-κB （P<0.01）， increased the serum IL-2 level （P<0.01）， and lowered the IL-6 and TNF-α levels （P<0.05， P<0.01）. M-JQD downregulated the mRNA level of NF-κB （P<0.01） and the protein level of p38 MAPK （P<0.05）， elevated the IL-2 level （P<0.01）， and lowered the TNF-α level （P<0.01）. ConclusionM- and H-JQD can prevent and control IAV infection-induced pneumonia dose-dependently by inhibiting the TLR7/MAPK/NF-κB signaling pathway， increasing IL-2， and reducing excessive secretion of IL-6 and TNF-α.

ObjectiveTo explore the mechanism of Jiebiao Qingli decoction （JQD） in treating pneumonia caused by influenza A virus （IAV） infection. MethodsA total of 132 Balb/c mice were randomly assigned into normal control （NC）， model control （IAV）， oseltamivir （OSV， 37.5 mg·kg^-1）， and high-， medium-， low-dose JQD （H-， M-， and L-JQD： 6.05， 3.02， and 1.51 g·kg^-1， respectively） groups. The NC group was treated with normal saline nasal drops， and the other groups were intranasally inoculated with A/Brisbane/02/2018 （H1N1） ［pdm09-like virus （H1N1）］ for the modeling of IAV infection. Two hours post-modeling， the NC and IAV groups were administrated with normal saline by gavage， while other groups received corresponding drugs for 7 d. The body mass， survival status， and deaths of mice were recorded daily during the administration of the drugs. On days 3 and 7， the lung index was measured for mice in each group. Pathological changes in the lung tissue were observed via hematoxylin-eosin staining. Real-time fluorescence quantitative polymerase chain reaction （Real-time PCR） was conducted to measure the viral load （IAV-M） and the mRNA levels of Toll-like receptor 7 （TLR7）， p38 mitogen-activated protein kinase （p38 MAPK）， and nuclear factor-kappa B （NF-κB） in the lung tissue. Western blot was employed to measure the protein levels of p38 MAPK and NF-κB. Enzyme-linked immunosorbent assay was used to quantify serum levels of interleukin-2 （IL-2）， interleukin-6 （IL-6）， and tumor necrosis factor-alpha （TNF-α）. ResultsCompared with the NC group， the IAV group showed reduced survival quality and survival days （P<0.01）， lung congestion， inflammatory cell infiltration， elevated lung index （P<0.01）， increased viral load （P<0.01）， upregulated TLR7， p38 MAPK， and NF-κB levels （P<0.05， P<0.01）， decreased IL-2 level （P<0.01）， and elevated IL-6 and TNF-α levels （P<0.01）. Compared with the IAV group， H-JQD prolonged survival days （P<0.05）. All JQD groups alleviated pathological changes in the lung tissue and reduced the lung index （P<0.01）. M-JQD and H-JQD decreased the viral load （P<0.01）. H-JQD downregulated the mRNA levels of TLR7， p38 MAPK， and NF-κB （P<0.05， P<0.01） and the protein levels of p38 MAPK and NF-κB （P<0.01）， increased the serum IL-2 level （P<0.01）， and lowered the IL-6 and TNF-α levels （P<0.05， P<0.01）. M-JQD downregulated the mRNA level of NF-κB （P<0.01） and the protein level of p38 MAPK （P<0.05）， elevated the IL-2 level （P<0.01）， and lowered the TNF-α level （P<0.01）. ConclusionM- and H-JQD can prevent and control IAV infection-induced pneumonia dose-dependently by inhibiting the TLR7/MAPK/NF-κB signaling pathway， increasing IL-2， and reducing excessive secretion of IL-6 and TNF-α.

Objective: Executive function correlates with the parasympathetic nervous system (PNS) based on static heart rate variability (HRV) measurements. Our study advances this understanding by employing dynamic assessments of the PNS to explore and quantify its relationship with inhibitory control (IC). Methods: We recruited 31 men aged 20–35 years. We monitored their electrocardiogram (ECG) signals during the administration of the Conners’ Continuous Performance Test-II (CCPT-II) on a weekly basis over 2 weeks. HRV analysis was performed on ECG-derived RR intervals using 5-minute windows, each overlapping for the next 4 minutes to establish 1-minute intervals. For each time window, the HRV metrics extracted were: mean RR intervals, standard deviation of NN intervals (SDNN), low-frequency power with logarithm (lnLF), and high-frequency power with logarithm (lnHF). Each value was correlated with detectability and compared to the corresponding baseline value at t0. Results: Compared with the baseline level, SDNN and lnLF showed marked decreases during CCPT-II. The mean values of HRV showed significant correlation with d’, including mean SDNN (R=0.474, p=0.012), mean lnLF (R=0.390, p=0.045), and mean lnHF (R=0.400, p=0.032). In the 14th time window, the significant correlations included SDNN (R=0.578, p=0.002), lnLF (R=0.493, p=0.012), and lnHF (R=0.432, p=0.031). Significant correlation between d’ and HRV parameters emerged only during the initial CCPT-II. Conclusion A significant correlation between PNS and IC was observed in the first session alone. The IC in the repeated CCPT-II needs to consider the broader neural network.

Purpose: Biomarkers predicting clinically significant prostate cancer (sPC) before biopsy are currently lacking. This study aimed to develop a non-invasive urine test to predict sPC in at-risk men using urinary metabolomic profiles. Materials and Methods: Urine samples from 934 at-risk subjects and 268 treatment-naïve PC patients were subjected to liquid chromatography/mass spectrophotometry (LC-MS)-based metabolomics profiling using both C18 and hydrophilic interaction liquid chromatography (HILIC) column analyses. Four models were constructed (training cohort [n=647]) and validated (validation cohort [n=344]) for different purposes. Model I differentiates PC from benign cases. Models II, III, and a Gleason score model (model GS) predict sPC that is defined as National Comprehensive Cancer Network (NCCN)-categorized favorable-intermediate risk group or higher (Model II), unfavorable-intermediate risk group or higher (Model III), and GS ≥7 PC (model GS), respectively. The metabolomic panels and predicting models were constructed using logistic regression and Akaike information criterion. Results: The best metabolomic panels from the HILIC column include 25, 27, 28 and 26 metabolites in Models I, II, III, and GS, respectively, with area under the curve (AUC) values ranging between 0.82 and 0.91 in the training cohort and between 0.77 and 0.86 in the validation cohort. The combination of the metabolomic panels and five baseline clinical factors that include serum prostate-specific antigen, age, family history of PC, previously negative biopsy, and abnormal digital rectal examination results significantly increased AUCs (range 0.88–0.91). At 90% sensitivity (validation cohort), 33%, 34%, 41%, and 36% of unnecessary biopsies were avoided in Models I, II, III, and GS, respectively. The above results were successfully validated using LC-MS with the C18 column. Conclusions Urinary metabolomic profiles with baseline clinical factors may accurately predict sPC in men with elevated risk before biopsy.

Background: and Purpose Symptomatic intracranial hemorrhage (sICH) following endovascular thrombectomy (EVT) is a severe complication associated with adverse functional outcomes and increased mortality rates. Currently, a reliable predictive model for sICH risk after EVT is lacking. Methods: This study used data from patients aged ≥20 years who underwent EVT for anterior circulation stroke from the nationwide Taiwan Registry of Endovascular Thrombectomy for Acute Ischemic Stroke (TREAT-AIS). A predictive model including factors associated with an increased risk of sICH after EVT was developed to differentiate between patients with and without sICH. This model was compared existing predictive models using nationwide registry data to evaluate its relative performance. Results: Of the 2,507 identified patients, 158 developed sICH after EVT. Factors such as diastolic blood pressure, Alberta Stroke Program Early CT Score, platelet count, glucose level, collateral score, and successful reperfusion were associated with the risk of sICH after EVT. The TREAT-AIS score demonstrated acceptable predictive accuracy (area under the curve [AUC]=0.694), with higher scores being associated with an increased risk of sICH (odds ratio=2.01 per score increase, 95% confidence interval=1.64–2.45, P<0.001). The discriminatory capacity of the score was similar in patients with symptom onset beyond 6 hours (AUC=0.705). Compared to existing models, the TREAT-AIS score consistently exhibited superior predictive accuracy, although this difference was marginal. Conclusions The TREAT-AIS score outperformed existing models, and demonstrated an acceptable discriminatory capacity for distinguishing patients according to sICH risk levels. However, the differences between models were only marginal. Further research incorporating periprocedural and postprocedural factors is required to improve the predictive accuracy.

Background: Intraoperative hypercapnia reduces the time to emergence from volatile anesthetics, but few clinical studies have explored the effect of hypercapnia on the emergence time from intravenous (IV) anesthesia. We investigated the effect of inducing mild hypercapnia during the recovery period on the emergence time after total IV anesthesia (TIVA). Methods: Adult patients undergoing transurethral lithotripsy under TIVA were randomly allocated to normocapnia group (end-tidal carbon dioxide [ETCO2] 35–40 mmHg) or mild hypercapnia group (ETCO2 50-55 mmHg) during the recovery period. The primary outcome was the extubation time. The spontaneous breathing-onset time, voluntary eye-opening time, and hemodynamic data were collected. Changes in the cerebral blood flow velocity in the middle cerebral artery were assessed using transcranial Doppler ultrasound. Results: In total, 164 patients completed the study. The extubation time was significantly shorter in the mild hypercapnia (13.9 ± 5.9 min, P = 0.024) than in the normocapnia group (16.3 ± 7.6 min). A similar reduction was observed in spontaneous breathing-onset time (P = 0.021) and voluntary eye-opening time (P = 0.008). Multiple linear regression analysis revealed that the adjusted ETCO2 level was a negative predictor of extubation time. Middle cerebral artery blood flow velocity was significantly increased after ETCO2 adjustment for mild hypercapnia, which rapidly returned to baseline, without any adverse reactions, within 20 min after extubation. Conclusions Mild hypercapnia during the recovery period significantly reduces the extubation time after TIVA. Increased ETCO2 levels can potentially enhance rapid recovery from IV anesthesia.

Purpose: Biomarkers predicting clinically significant prostate cancer (sPC) before biopsy are currently lacking. This study aimed to develop a non-invasive urine test to predict sPC in at-risk men using urinary metabolomic profiles. Materials and Methods: Urine samples from 934 at-risk subjects and 268 treatment-naïve PC patients were subjected to liquid chromatography/mass spectrophotometry (LC-MS)-based metabolomics profiling using both C18 and hydrophilic interaction liquid chromatography (HILIC) column analyses. Four models were constructed (training cohort [n=647]) and validated (validation cohort [n=344]) for different purposes. Model I differentiates PC from benign cases. Models II, III, and a Gleason score model (model GS) predict sPC that is defined as National Comprehensive Cancer Network (NCCN)-categorized favorable-intermediate risk group or higher (Model II), unfavorable-intermediate risk group or higher (Model III), and GS ≥7 PC (model GS), respectively. The metabolomic panels and predicting models were constructed using logistic regression and Akaike information criterion. Results: The best metabolomic panels from the HILIC column include 25, 27, 28 and 26 metabolites in Models I, II, III, and GS, respectively, with area under the curve (AUC) values ranging between 0.82 and 0.91 in the training cohort and between 0.77 and 0.86 in the validation cohort. The combination of the metabolomic panels and five baseline clinical factors that include serum prostate-specific antigen, age, family history of PC, previously negative biopsy, and abnormal digital rectal examination results significantly increased AUCs (range 0.88–0.91). At 90% sensitivity (validation cohort), 33%, 34%, 41%, and 36% of unnecessary biopsies were avoided in Models I, II, III, and GS, respectively. The above results were successfully validated using LC-MS with the C18 column. Conclusions Urinary metabolomic profiles with baseline clinical factors may accurately predict sPC in men with elevated risk before biopsy.