Background Fine particulate matter (PM_2.5) monitoring stations may generate missing data for a certain period of time due to various factors. This data loss will adversely affect air quality assessment and pollution control decision-making. Objective To propose an inverse distance weighted (IDW) spatiotemporal interpolation method based on particle swarm optimization (PSO) to interpolate and fill missing PM_2.5 spatiotemporal sequence data and increase interpolation accuracy. Methods An interpolation experiment was designed into two parts. The first part used hourly PM_2.5 observational data from four moments on January 1, 2017 in the Yangtze River Delta region. The second part employed daily PM_2.5 observational data from the first 10 d of January 2017 in the Beijing-Tianjin-Hebei region. Interpolation accuracy was evaluated using four metrics: root mean square error (RMSE), mean absolute error (MAE), mean absolute percentage error (MAPE), and mean relative error (MRE). Results IDW spatiotemporal interpolation method optimized with PSO significantly improved the accuracy of filling missing PM_2.5 spatiotemporal sequence data. In the hourly-scale experiment conducted in the Yangtze River Delta region, compared to a distance index of 2, the accuracy metrics RMSE, MAE, MAPE, and MRE generated by the proposed method improved on average by 0.17 μg·m⁻³, 0.27 μg·m⁻³, 0.17%, and 0.01%, respectively. The PM_2.5 spatial field maps generated for four moments based on this method clearly illustrated the spatiotemporal distribution characteristics of hourly PM_2.5 concentrations in the Yangtze River Delta region. In the daily-scale experiment conducted in the Beijing-Tianjin-Hebei region, the PSO-optimized distance index outperformed the traditional method, with interpolation accuracy improvements of approximately 0.215 μg·m⁻³, 0.283 μg·m⁻³, 0.174%, and 0.014%, respectively. Furthermore, the seasonal PM_2.5 spatial field maps generated by this method revealed the spatiotemporal distribution characteristics of PM_2.5 concentrations in the Beijing-Tianjin-Hebei region across different seasons, further validating the effectiveness and applicability of this method. Conclusion The IDW spatiotemporal interpolation method optimized with PSO is highly accurate and reliable for interpolating the missing data in the Yangtze River Delta region and the Beijing-Tianjin-Hebei region, providing valuable insights for air pollution control and public health protection.

Objective To investigate the setup error in patients with spinal bone metastasis who underwent radiotherapy under the guidance of kilovoltage cone-beam CT (KV-CBCT). Methods A total of 118 patients with spinal metastasis who underwent radiotherapy, including 17 cases of cervical spine, 62 cases of thoracic spine, and 39 cases of lumbar spine, were collected. KV-CBCT scans were performed using the linear accelerators from Elekta and Varian’s EDGE system. CBCT images were registered with reference CT images in the bone window mode. A total of 973 data were collected, and 3D linear errors were recorded. Results The patients with spinal bone metastasis were grouped by site, height, weight, and BMI. The P value of the patients grouped only by site was P<0.05, which was statistically significant. Conclusion When grouped by site in the 3D direction, the positioning effect of cervical spine is better than that of thoracic and lumbar spine. The positioning effect of the thoracic spine is better in the head and foot direction but worse in the left and right direction compared with that of the lumbar spine. Instead of extending or narrowing the margin according to the BMI of patients with spinal metastasis, the margin must be changed according to the site of spinal bone metastasis.

This study established a high performance liquid chromatography(HPLC) fingerprint of Chuanxiong Rhizoma from different producing areas and screened its potential differential components for producing areas by chemometrics. Furthermore, the content of the above differential components in Chuanxiong Rhizoma from different producing areas was measured and compared. Then, the geoherbalism markers(geo-markers) that can be used to distinguish Dao-di and non-Dao-di Chuanxiong Rhizoma were excavated by chemometrics. In fingerprint studies, a total of 27 common peaks were determined, and the fingerprint similarity for 37 batches of Chuanxiong Rhizoma samples from different producing areas was above 0.968. The orthogonal partial least squares-discriminant analysis(OPLS-DA) was capable of distinguishing Chuanxiong Rhizoma from Sichuan and from three other provinces, as well as Dao-di Chuanxiong Rhizoma(from Dujiangyan) and non-Dao-di Chuanxiong Rhizoma(from other producing areas) in Sichuan province. Meanwhile, 14 potential differential components in Chuanxiong Rhizoma from different provinces and 16 potential differential components in Chuanxiong Rhizoma from different producing areas in Sichuan were screened by the variable importance in projection(VIP) analysis under OPLS-DA. The reference standards were used to identify 10 potential differential components in the common peaks, and subsequent content determination verified that the content of the above 10 potential differential components was different among different producing areas. Then, the OPLS-DA and VIP analysis were performed with the content of the 10 potential differential components as variables. The results showed that Z-ligustilide, chlorogenic acid, and the ratio of butylidenephthalide/senkyunolide A were the geo-markers that can distinguish Chuanxiong Rhizoma from Sichuan and Chuanxiong Rhizoma from Shaanxi, Hebei, and Jiangxi, while Z-ligustilide, n-butylphthalide, and the ratios of Z-ligustilide/senkyunolide A and butylidenephthalide/senkyunolide A were the geo-markers that can distinguish Dao-di Chuanxiong Rhizoma(from Dujiangyan) and non-Dao-di Chuanxiong Rhizoma(from other producing areas) in Sichuan province. This study elucidated the differences in material basis of Dao-di and non-Dao-di Chuanxiong Rhizoma based on fingerprinting and content determination combined with chemometrics, which provides a reference for the study of material basis of Dao-di traditional Chinese medicine.
Drugs, Chinese Herbal/chemistry* ; Rhizome/chemistry* ; Chromatography, High Pressure Liquid/methods* ; Chemometrics/methods* ; Quality Control

OBJECTIVE: To explore the effect of bear bile powder (BBP) on acute lung injury (ALI) and the underlying mechanism. METHODS: The chemical constituents of BBP were analyzed by ultra-high-pressure liquid chromatography-mass spectrometry (UPLC-MS). After 7 days of adaptive feeding, 50 mice were randomly divided into 5 groups by a random number table (n=10): normal control (NC), lipopolysaccharide (LPS), dexamethasone (Dex), low-, and high-dose BBP groups. The dosing cycle was 9 days. On the 12th and 14th days, 20 µL of Staphylococcus aureus solution (bacterial concentration of 1 × 10^-7 CFU/mL) was given by nasal drip after 1 h of intragastric administration, and the mice in the NC group was given the same dose of phosphated buffered saline (PBS) solution. On the 16th day, after 1 h intragastric administration, 100 µL of LPS solution (1 mg/mL) was given by tracheal intubation, and the same dose of PBS solution was given to the NC group. Lung tissue was obtained to measure the myeloperoxidase (MPO) activity, the lung wet/dry weight ratio and expressions of CD14 and other related proteins. The lower lobe of the right lung was obtained for pathological examination. The concentrations of inflammatory cytokines including interleukin (IL)-6, tumour necrosis factor α (TNF-α ) and IL-1β in the bronchoalveolar lavage fluid (BALF) were detected by enzyme linked immunosorbent assay, and the number of neutrophils was counted. The colonic contents of the mice were analyzed by 16 sRNA technique and the contents of short-chain fatty acids (SCFAs) were measured by gas chromatograph-mass spectrometer (GC-MS). RESULTS: UPLC-MS revealed that the chemical components of BBP samples were mainly tauroursodeoxycholic acid and taurochenodeoxycholic acid sodium salt. BBP reduced the activity of MPO, concentrations of inflammatory cytokines, and inhibited the expression of CD14 protein, thus suppressing the activation of NF-κB pathway (P<0.05). The lung histopathological results indicated that BBP significantly reduced the degree of neutrophil infiltration, cell shedding, necrosis, and alveolar cavity depression. Moreover, BBP effectively regulated the composition of the intestinal microflora and increased the production of SCFAs, which contributed to its treatment effect (P<0.05). CONCLUSIONS BBP alleviates lung injury in ALI mouse through inhibiting activation of NF-κB pathway and decreasing expression of CD14 protein. BBP may promote recovery of ALI by improving the structure of intestinal flora and enhancing metabolic function of intestinal flora.
Animals ; Acute Lung Injury/pathology* ; Lipopolysaccharides ; Ursidae ; Gastrointestinal Microbiome/drug effects* ; Bile/chemistry* ; Lipopolysaccharide Receptors/metabolism* ; Powders ; Male ; Lung/drug effects* ; Mice ; Peroxidase/metabolism* ; Signal Transduction/drug effects* ; Cytokines/metabolism*

Colorectal cancer (CRC) poses a severe global health challenge with high incidence and mortality rates. USP37 has been identified as the bona fide deubiquitinase of SND1, playing a critical role in stabilizing SND1, thereby augmenting its oncogenic potential. The interaction between USP37 and SND1 was confirmed through extensive proteomics, ubiquitinomics, and interactomics, underscoring their synergistic effects on CRC proliferation and metastasis. Additionally, CDK1 has emerged as a pivotal regulator of USP37, phosphorylating it at threonine 631 rather than serine 628, enhancing its deubiquitinase activity, and consequently stabilizing SND1 to drive CRC malignancy further. Histological analyses of human CRC samples linked the upregulation of CDK1 and USP37 with increased SND1 levels and poor patient prognosis. High-throughput virtual screening and subsequent experimental validation identified Dacarbazine as a pharmacological inhibitor of USP37, and its inhibition disrupted SND1 stability, hindering CRC cell proliferation and metastasis. This study reveals a novel and promising molecular mechanism driving CRC progression through the CDK1-USP37-SND1 axis, highlighting the clinical importance of targeting this pathway to improve patient outcomes.

Protein liquid-liquid phase separation (LLPS), a pivotal phenomenon intricately linked to cellular processes, is regulated by various other proteins. However, there is still a lack of high-throughput methods for screening protein regulators of LLPS in target proteins. Here, we developed a CRISPR/Cas9-based screening method to identify protein phase separation regulators by integrating bimolecular fluorescence complementation (BiFC) and fluorescence-activated cell sorting (FACS). Using this newly developed method, we screened the RNA-binding proteins that regulate PABPN1 phase separation and identified the tumor suppressor QKI as a promoter of PABPN1 phase separation. Furthermore, QKI exhibits decreased expression levels and diminished nuclear localization in colorectal cancer cells, resulting in reduced PABPN1 phase separation, which, in turn, promotes alternative polyadenylation (APA), cell proliferation, and migration in colorectal cancer.
Humans ; Colorectal Neoplasms/genetics* ; RNA-Binding Proteins/genetics* ; Poly(A)-Binding Protein I/genetics* ; CRISPR-Cas Systems ; Flow Cytometry ; Cell Proliferation ; Cell Line, Tumor ; Cell Movement

Peganum harmala L. (P. harmala) is a significant economic and medicinal plant. The seeds of P. harmala have been extensively utilized in traditional Chinese medicine, Uighur medicine, and Mongolian medicine, as documented in the Drug Standard of the Ministry of Health of China. Twelve novel tryptamine-derived alkaloids (1-12) and eight known compounds (13-20) were isolated from P. harmala seeds. Compounds 1 and 2 represent the first reported instances of tryptamine-derived heteromers, comprising tryptamine and aniline fragments with previously undocumented C-3-N-1' linkage and C-3-C-4' connection, respectively. Compounds 3-5 were identified as indole-quinazoline heteromers, exhibiting a novel C-3 and NH-1' linkage between indole and quinazoline-derived fragments. Compound 6 demonstrates the dimerization pattern of C-C linked tryptamine-quinazoline dimer. Compound 8 represents a tryptamine-derived heterodimer with a distinctive carbon skeleton, featuring an unusual spiro-tricyclic ring (7) and conventional bicyclic tryptamine. Compounds 9-11 constitute novel 6/5/5/5 spiro-tetracyclic tryptamine-derived alkaloids presenting a unique ring system of tryptamine-spiro-pyrrolizine. Compounds 1-3 and 6-11 were identified as racemates. Compounds 2, 7, 9, 10, and 12 were confirmed via X-ray crystallographic analysis. All isolated compounds (1-20) exhibited varying degrees of antiviral efficacy against respiratory syncytial virus (RSV). Notably, the anti-RSV activity of compound 12 (IC₅₀ 5.01 ± 0.14 μmol·L^-1) surpassed that of the positive control (ribavirin, IC₅₀ 6.23 ± 0.95 μmol·L^-1), as validated through plaque reduction and immunofluorescence assays. The identification of anti-RSV compounds from P. harmala seeds may enhance the development and application of this plant in antiviral therapeutic products.
Antiviral Agents/isolation & purification* ; Tryptamines/isolation & purification* ; Peganum/chemistry* ; Seeds/chemistry* ; Alkaloids/isolation & purification* ; Molecular Structure ; Humans ; Respiratory Syncytial Viruses/drug effects* ; Plant Extracts/pharmacology* ; Drugs, Chinese Herbal/pharmacology*

Interventions for endometriosis(EMs)include surgical excision of lesions and hormonal therapy,which usually have limited efficacy and adverse drug reactions.Traditional Chinese medicine(TCM)has the multi-component and multi-target characteristics,which can help patients achieve good clinical benefits by intervening in different parts of the disease.In this paper,we briefly discuss the modern pharmacology of Sanlang and Curcuma longa,and deeply summarize the possible mechanisms of action of TCM monomer and classical compound extracts and their active ingredients through signal pathways in inflammation,immune system,angiogenesis,hormone regulation,etc.,so as to provide theoretical bases for the clinical use of TCM monomers,drug-to-drug groups and compounds in the treatment of EMs.

Objective:To investigate the status of medical care seeking delay and diagnosis delay of pulmonary tuberculosis (PTB) patients in Tongzhou District and Changping District of Beijing, analyze the related factors and put forward suggestions for early detection and scientific management of PTB patients.Methods:A retrospective epidemiological survey was conducted to collect the incidence data of PTB registered in Tongzhou and Changping from January 1 to December 31, 2021 by using the Chinese Tuberculosis Information Management System, and telephone interview were used for information supplement. Multivariate logistic regression model and decision tree model were used to analyze the influencing factors of medical care seeking delay and diagnosis delay of PTB patients.Results:In 2021, the medical care seeking delay time M( Q1, Q3) in the PTB patients in Tongzhou and Changping was 11 (5, 26) days, with a delay rate of 41.71%. Results from multivariate logistic regression model analysis revealed that factors influencing the medical care seeking delay included regular health check-up ( OR=0.033, 95% CI: 0.008-0.147), coughing for less than 2 weeks or showing any symptom of PTB before medical care seeking ( OR=0.378, 95% CI: 0.215-0.665), showing other symptoms before medical care seeking( OR=2.791, 95% CI: 1.710-4.555), no work or school in medical care seeking ( OR=2.990, 95% CI: 1.419-6.298). The diagnosis delay time M( Q1, Q3) in the PTB patients was 8 (0, 18) days, with a delay rate of 35.20%. Multivariate logistic regression model analysis revealed that the factors influencing the diagnosis delay of PTB included being diagnosed at a specialized tuberculosis hospital ( OR=0.426, 95% CI: 0.236-0.767) or a tuberculosis prevention and control institution ( OR=1.843, 95% CI: 1.061-3.202) and being traced as a source of infection ( OR=2.632, 95% CI: 1.062-6.521). The overall performance of the multivariate logistic regression model was comparable to that of the decision tree model, with the decision tree model exhibiting higher sensitivity but lower specificity. Conclusions:The medical care seeking delay rate and diagnosis delay rate of tuberculosis in Tongzhou and Changping were at low levels in 2021. However, it is still necessary to strengthen the health education and active screening, improve the public awareness of PTB prevention and control, and further improve the level of medical services and medical access to reduce the medical care seeking delay and diagnosis delay of PTB patients.

Background::In vitro fertilization (IVF) has emerged as a transformative solution for infertility. However, achieving favorable live-birth outcomes remains challenging. Current clinical IVF practices in IVF involve the collection of heterogeneous embryo data through diverse methods, including static images and temporal videos. However, traditional embryo selection methods, primarily reliant on visual inspection of morphology, exhibit variability and are contingent on the experience of practitioners. Therefore, an automated system that can evaluate heterogeneous embryo data to predict the final outcomes of live births is highly desirable. Methods::We employed artificial intelligence (AI) for embryo morphological grading, blastocyst embryo selection, aneuploidy prediction, and final live-birth outcome prediction. We developed and validated the AI models using multitask learning for embryo morphological assessment, including pronucleus type on day 1 and the number of blastomeres, asymmetry, and fragmentation of blastomeres on day 3, using 19,201 embryo photographs from 8271 patients. A neural network was trained on embryo and clinical metadata to identify good-quality embryos for implantation on day 3 or day 5, and predict live-birth outcomes. Additionally, a 3D convolutional neural network was trained on 418 time-lapse videos of preimplantation genetic testing (PGT)-based ploidy outcomes for the prediction of aneuploidy and consequent live-birth outcomes.Results::These two approaches enabled us to automatically assess the implantation potential. By combining embryo and maternal metrics in an ensemble AI model, we evaluated live-birth outcomes in a prospective cohort that achieved higher accuracy than experienced embryologists (46.1% vs. 30.7% on day 3, 55.0% vs. 40.7% on day 5). Our results demonstrate the potential for AI-based selection of embryos based on characteristics beyond the observational abilities of human clinicians (area under the curve: 0.769, 95% confidence interval: 0.709–0.820). These findings could potentially provide a noninvasive, high-throughput, and low-cost screening tool to facilitate embryo selection and achieve better outcomes. Conclusions::Our study underscores the AI model’s ability to provide interpretable evidence for clinicians in assisted reproduction, highlighting its potential as a noninvasive, efficient, and cost-effective tool for improved embryo selection and enhanced IVF outcomes. The convergence of cutting-edge technology and reproductive medicine has opened new avenues for addressing infertility challenges and optimizing IVF success rates.