The CyberKnife, an acronym for the stereotactic radiosurgery platform, represents an image-guided stereotactic radiotherapy technique. This technology precisely delivers ionizing radiation to tissues, effectively damaging tumor cells, and is suitable for radiotherapy of both intracranial and extracranial tumors. This article reports the first performance of CyberKnife by radiotherapy at Peking Union Medical College Hospital, including a patient with uncontrolled pituitary adenoma after surgery and radiotherapy, and another patient with vertebral metastasis following targeted therapy for lung adenocarcinoma. The application of CyberKnife technology in radiotherapy has achieved highly accurate dose delivery, enabling targeted irradiation of tumor lesions while minimizing damage to surrounding normal tissues, thereby yielding relatively ideal clinical outcomes.

Objective: To evaluate the feasibility of dynamic contrast-enhanced MRI (DCE-MRI) in differentiating tumor deposits (TDs) from metastatic lymph nodes (MLNs) in rectal cancer. Materials and Methods: A retrospective analysis was conducted on 70 patients with rectal cancer, including 168 lesions (70 TDs and 98 MLNs confirmed by histopathology), who underwent pretreatment MRI and subsequent surgery between March 2019 and December 2022. The morphological characteristics of TDs and MLNs, along with quantitative parameters derived from DCE-MRI (K trans , kep, and v e) and DWI (ADCmin, ADCmax, and ADCmean), were analyzed and compared between the two groups.Multivariable binary logistic regression and receiver operating characteristic (ROC) curve analyses were performed to assess the diagnostic performance of significant individual quantitative parameters and combined parameters in distinguishing TDs from MLNs. Results: All morphological features, including size, shape, border, and signal intensity, as well as all DCE-MRI parameters showed significant differences between TDs and MLNs (all P < 0.05). However, ADC values did not demonstrate significant differences (all P > 0.05). Among the single quantitative parameters, v e had the highest diagnostic accuracy, with an area under the ROC curve (AUC) of 0.772 for distinguishing TDs from MLNs. A multivariable logistic regression model incorporating short axis, border, v e, and ADC mean improved diagnostic performance, achieving an AUC of 0.833 (P = 0.027). Conclusion The combination of morphological features, DCE-MRI parameters, and ADC values can effectively aid in the preoperative differentiation of TDs from MLNs in rectal cancer.

Objective: To evaluate the feasibility of dynamic contrast-enhanced MRI (DCE-MRI) in differentiating tumor deposits (TDs) from metastatic lymph nodes (MLNs) in rectal cancer. Materials and Methods: A retrospective analysis was conducted on 70 patients with rectal cancer, including 168 lesions (70 TDs and 98 MLNs confirmed by histopathology), who underwent pretreatment MRI and subsequent surgery between March 2019 and December 2022. The morphological characteristics of TDs and MLNs, along with quantitative parameters derived from DCE-MRI (K trans , kep, and v e) and DWI (ADCmin, ADCmax, and ADCmean), were analyzed and compared between the two groups.Multivariable binary logistic regression and receiver operating characteristic (ROC) curve analyses were performed to assess the diagnostic performance of significant individual quantitative parameters and combined parameters in distinguishing TDs from MLNs. Results: All morphological features, including size, shape, border, and signal intensity, as well as all DCE-MRI parameters showed significant differences between TDs and MLNs (all P < 0.05). However, ADC values did not demonstrate significant differences (all P > 0.05). Among the single quantitative parameters, v e had the highest diagnostic accuracy, with an area under the ROC curve (AUC) of 0.772 for distinguishing TDs from MLNs. A multivariable logistic regression model incorporating short axis, border, v e, and ADC mean improved diagnostic performance, achieving an AUC of 0.833 (P = 0.027). Conclusion The combination of morphological features, DCE-MRI parameters, and ADC values can effectively aid in the preoperative differentiation of TDs from MLNs in rectal cancer.

Objective: To evaluate the feasibility of dynamic contrast-enhanced MRI (DCE-MRI) in differentiating tumor deposits (TDs) from metastatic lymph nodes (MLNs) in rectal cancer. Materials and Methods: A retrospective analysis was conducted on 70 patients with rectal cancer, including 168 lesions (70 TDs and 98 MLNs confirmed by histopathology), who underwent pretreatment MRI and subsequent surgery between March 2019 and December 2022. The morphological characteristics of TDs and MLNs, along with quantitative parameters derived from DCE-MRI (K trans , kep, and v e) and DWI (ADCmin, ADCmax, and ADCmean), were analyzed and compared between the two groups.Multivariable binary logistic regression and receiver operating characteristic (ROC) curve analyses were performed to assess the diagnostic performance of significant individual quantitative parameters and combined parameters in distinguishing TDs from MLNs. Results: All morphological features, including size, shape, border, and signal intensity, as well as all DCE-MRI parameters showed significant differences between TDs and MLNs (all P < 0.05). However, ADC values did not demonstrate significant differences (all P > 0.05). Among the single quantitative parameters, v e had the highest diagnostic accuracy, with an area under the ROC curve (AUC) of 0.772 for distinguishing TDs from MLNs. A multivariable logistic regression model incorporating short axis, border, v e, and ADC mean improved diagnostic performance, achieving an AUC of 0.833 (P = 0.027). Conclusion The combination of morphological features, DCE-MRI parameters, and ADC values can effectively aid in the preoperative differentiation of TDs from MLNs in rectal cancer.

Objective: To evaluate the feasibility of dynamic contrast-enhanced MRI (DCE-MRI) in differentiating tumor deposits (TDs) from metastatic lymph nodes (MLNs) in rectal cancer. Materials and Methods: A retrospective analysis was conducted on 70 patients with rectal cancer, including 168 lesions (70 TDs and 98 MLNs confirmed by histopathology), who underwent pretreatment MRI and subsequent surgery between March 2019 and December 2022. The morphological characteristics of TDs and MLNs, along with quantitative parameters derived from DCE-MRI (K trans , kep, and v e) and DWI (ADCmin, ADCmax, and ADCmean), were analyzed and compared between the two groups.Multivariable binary logistic regression and receiver operating characteristic (ROC) curve analyses were performed to assess the diagnostic performance of significant individual quantitative parameters and combined parameters in distinguishing TDs from MLNs. Results: All morphological features, including size, shape, border, and signal intensity, as well as all DCE-MRI parameters showed significant differences between TDs and MLNs (all P < 0.05). However, ADC values did not demonstrate significant differences (all P > 0.05). Among the single quantitative parameters, v e had the highest diagnostic accuracy, with an area under the ROC curve (AUC) of 0.772 for distinguishing TDs from MLNs. A multivariable logistic regression model incorporating short axis, border, v e, and ADC mean improved diagnostic performance, achieving an AUC of 0.833 (P = 0.027). Conclusion The combination of morphological features, DCE-MRI parameters, and ADC values can effectively aid in the preoperative differentiation of TDs from MLNs in rectal cancer.

Objective: To evaluate the feasibility of dynamic contrast-enhanced MRI (DCE-MRI) in differentiating tumor deposits (TDs) from metastatic lymph nodes (MLNs) in rectal cancer. Materials and Methods: A retrospective analysis was conducted on 70 patients with rectal cancer, including 168 lesions (70 TDs and 98 MLNs confirmed by histopathology), who underwent pretreatment MRI and subsequent surgery between March 2019 and December 2022. The morphological characteristics of TDs and MLNs, along with quantitative parameters derived from DCE-MRI (K trans , kep, and v e) and DWI (ADCmin, ADCmax, and ADCmean), were analyzed and compared between the two groups.Multivariable binary logistic regression and receiver operating characteristic (ROC) curve analyses were performed to assess the diagnostic performance of significant individual quantitative parameters and combined parameters in distinguishing TDs from MLNs. Results: All morphological features, including size, shape, border, and signal intensity, as well as all DCE-MRI parameters showed significant differences between TDs and MLNs (all P < 0.05). However, ADC values did not demonstrate significant differences (all P > 0.05). Among the single quantitative parameters, v e had the highest diagnostic accuracy, with an area under the ROC curve (AUC) of 0.772 for distinguishing TDs from MLNs. A multivariable logistic regression model incorporating short axis, border, v e, and ADC mean improved diagnostic performance, achieving an AUC of 0.833 (P = 0.027). Conclusion The combination of morphological features, DCE-MRI parameters, and ADC values can effectively aid in the preoperative differentiation of TDs from MLNs in rectal cancer.

ObjectiveThe differential expression of microRNAs （miRNAs） between the active stage and the remission stage of ulcerative colitis （UC） was analyzed by bioinformatics method， and the regulatory relationship was constructed by screening the differentially expressed genes （DEGs）. The mechanism of Xizhuo Jiedu recipe in the treatment of UC was speculated and verified by animal experiments. MethodThe miRNAs data set of colonic mucosa tissue of UC patients was obtained from the gene expression database （GEO）， and the most differentially expressed miRNAs were screened by GEO2R， Excel， and other tools as research objects. TargetScan， miRTarbase， miRDB， STRING， TRRUST， and Matescape databases were used to screen key DEGs， predict downstream transcription factors （TFs）， gene ontology （GO）， and conduct Kyoto Encyclopedia of Genes and Genomes （KEGG） enrichment analysis. The key signaling pathways were selected for animal experiments. In animal experiments， the UC mouse model was prepared by making the mouse freely drink 2.5% dextran sodium sulfate （DSS）. Xiezhu Jiedu recipe and mesalazine were given by gavage for seven days， and the inflammatory infiltration of colonic mucosa was observed by hematoxylin-eosin （HE） staining. Real-time fluorescence quantitative polymerase chain reaction （Real-time PCR） was used to detect the mRNA expression of miR-155-5p in colon tissue. Immunohistochemistry and Western blot were used to detect the protein expression levels of cytokine signal transduction inhibitor （SOCS1）， phosphorylated transcriptional signal transductor and activator 3 （p-STAT3）， phosphorylated Janus kinase 2 （p-JAK2）， and retinoic acid-associated orphan receptor-γt （ROR-γt）. The expression levels of transforming growth factor-β （TGF-β）， interleukin-17 （IL-17）， interleukin-6 （IL-6）， and interleukin-10 （IL-10） in serum were detected by enzyme linked immunosorbent assay （ELISA）. ResultThe GSE48957 dataset was screened from the GEO database， and miR-155-5p was selected as the research object from the samples in the active and remission stages. 131 DEGs were screened. The GO/KEGG enrichment analysis was closely related to biological processes such as positive regulation of miRNA transcription and protein phosphorylation， as well as signaling pathways such as stem cell signaling pathway， IL-17 signaling pathway， and helper T cell 17 （Th17） cell differentiation. The Matescape database was used to screen out 10 key DEGs， among which SOCS1 was one of the key DEGs of miR-155-5p. Further screening of the TFS of key DEGs revealed that STAT3 was one of the main TFs of SOCS1. The results of animal experiments showed that Xiezhu Jiedu Recipe could effectively down-regulate the mRNA expression of miR-155-5p and protein expression of p-STAT3， p-JAK2， and ROR-γt in colon tissue of UC mice and the expression of IL-17 and IL-6 in serum of UC mice， up-regulate the protein expression of SOCS1 and the expression of TGF-β and IL-10， increase the level of anti-inflammatory factors， and reduce inflammatory cell infiltration. ConclusionIt is speculated that Xizhuo Jiedu recipe may interfere with SOCS1 by regulating the expression of miR-155-5p in UC mice， inhibit the phosphorylation of STAT3， inhibit the differentiation of CD4⁺ T cells into Th17 cells， reduce the levels of pro-inflammatory factors （IL-17 and IL-6）， and increase the levels of anti-inflammatory factors （TGF-β and IL-10）. As a result， the inflammation of colon mucosa in UC mice was alleviated.

Human physiological indicators have become an important standard for assessing health in modern society.Traditional detection methods often require a separate laboratory,complex operation process and long detection time,so it is urgent to develop portable,fast and accurate on-site detection technologies for bioanalysis.Point-of-care testing(POCT),which differs from traditional laboratory testing,can realize the rapid in situ detection of biomarkers without the complicated analytical process of the laboratory.Smartphones,which are an essential tool in our daily life,not only have independent operating systems and built-in storage functions,but also have high-definition cameras,which have great application potential in POCT visualization.The combination of various biosensing technologies and smartphones has developed into a new direction in the field of POCT.This review mainly introduced the research progress of smartphone-based visual biosensors in POCT in recent years,including colorimetric sensors,fluorescence sensors,chemiluminescence sensors and electrochemiluminescence sensors.Finally,the problems faced by smart-phone-based visual biosensors in the application of POCT were summarized,and their future development was prospected.

The correct pairing of disulfide bonds maintains the correct folding mode and high-level structure formation of peptides and protein drugs, which is crucial for the quality control of products. In order to ensure that the disulfide bonds are correctly paired, disulfide bond analysis is an essential part of peptides and protein drug characterization. Mass spectrometry can be used to analyze disulfide bonds. However, insulin and its analogues have two pairs of disulfide bonds without restriction enzyme cutting site. Conventional collision-induced dissociation (CID) and high-energy induced cleavage (HCD) cannot accurately locate the complex disulfide bond. In our study, three methods were used to localize the complex disulfide, including enzyme digestion combined with key peptide fragment in source decay (ISD) fragmentation method, enzyme digestion combined with partial reduction alkylation method, intact protein source ISD and electron transfer dissociation (ETD) cleavage method, The applicability of insulin aspart, insulin lispro and insulin glargine were also investigated. This study provides a new way for the quality control of disulfide bonding mode of insulin and its analogues, and also provides a reference for the disulfide bond localization of peptides or proteins containing this complex disulfide bond.

Objective:To establish biological exposure index (BEI) of occupational exposure to arsenic and its inorganic compounds through occupational epidemiology and the regression analysis of internal and external exposure of workers.Methods:In November 2021, 125 workers with occupational exposure to arsenic and its inorganic compounds and 49 office administrators in a non-ferrous metal smelter in Yunnan Province were selected as the exposure group and control group, respectively. Air samples from the workplace of the study subjects on weekdays were collected and arsenic concentrations were determined. Urine samples were collected in end-of-work weekend and high performance liquid chromatography-inductively coupled plasma mass spectrometry (HPLC-ICP-MS) was used to detect the levels of trivalent inorganic arsenic (iAs 3+) , pentavalent inorganic arsenic (iAs 5+) , monomethyl arsenic (MMA) and dimethyl arsenic (DMA) in urine. The correlations between arsenic concentration in the workplace air and arsenic species in urine of workers were analyzed. Arsenic exposure concentration and the level of urinary arsenic (∑iAs+MMA+DMA) of workers was analyzed by linear regression and the BEI of arsenic and its inorganic compounds in the workplace was proposed based on the results of micronucleus test. Results:The median of time-weighted average concentration ( CTWA) of arsenic in the workplace air of the exposure group was 0.0116 mg/m 3, and the over-standard rate was 71.2% (89/125) . The concentrations of iAs 3+, iAs 5+, inorganic arsenic (iAs=∑iAs 3++iAs 5+) 、MMA、DMA and urinary arsenic in the exposure group were higher than those in the control group at the end of shift, and the differences were statistically significant ( P<0.05) . The concentration of arsenic in the workplace air had the strongest correlation with the concentration of urinary arsenic at the end of the shift ( rs=0.909, P<0.001) . The regression equation was lg ( y) =7.662+2.968lg ( x) ( r=0.821, P<0.05) . According to the occupational exposure limit (OEL) of arsenic in China, the concentration of urinary arsenic in the end-of-work weekend was calculated to be 53.2 μg/L. Combined with the results of micronucleus test, the BEI of occupational exposure to arsenic and its inorganic compounds in the workplace was proposed to be 50 μg/L. Conclusion:The urinary arsenic in the end-of-work weekend can be used as a biomarker of occupational exposure to arsenic, and its BEI is recommended to be 50 μg/L.