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 proteome of biological evidence contains rich genetic information, namely single amino acid polymorphisms (SAPs) in protein sequences. However, due to the lack of efficient and convenient analysis tools, the application of SAP in public security still faces many challenges. This paper aims to meet the application requirements of SAP analysis for forensic biological evidence’s proteome data. MethodsThe software is divided into three modules. First, based on a built-in database of common non-synonymous single nucleotide polymorphisms (nsSNPs) and SAPs in East Asian populations, the software integrates and annotates newly identified exonic nsSNPs as SAPs, thereby constructing a customized SAP protein sequence database. It then utilizes a pre-installed search engine—either pFind or MaxQuant—to perform analysis and output SAP typing results, identifying both reference and variant types, along with their corresponding imputed nsSNPs. Finally, SAPTyper compares the proteome-based typing results with the individual’s exome-derived nsSNP profile and outputs the comparison report. ResultsSAPTyper accepts proteomic DDA mass spectrometry raw data (DDA acquisition mode) and exome sequencing results of nsSNPs as input and outputs the report of SAPs result. The pFind and Maxquant search engines were used to test the proteome data of 2 hair shafts of2 individuals, and both obtained SAP results. It was found that the results of the Maxquant search engine were slightly less than those of pFind. This result shows that SAPTyper can achieve SAP fingding function. Moreover, the pFind search engine was used to test the proteome data of 3 hair shafts from 1 European person and 1 African person in the literature. Among the sites fully matched by the literature method, sites detected by SAPTyper are also included; for semi-matching sites, that is, nsSNPs are heterozygous, both literature method and SAPTyper method had the risk of missing detection for one type of the allele. Comparing the analysis results of SAPTyper with the SAP test results reported in the literature, it was found that some imputed nsSNP sites identified by the literature method but not detected by SAPTyper had a MAF of less than 0.1% in East Asian populations, and therefore they were not included in the common nsSNP database of East Asian populations constructed by this software. Since the database construction of this software is based on the genetic variation information of East Asian populations, it is currently unable to effectively identify representative unique common variation sites in European or African populations, but it can still identify SAP sites shared by these populations and East Asian populations. ConclusionAn automated SAP analysis algorithm was developed for East Asian populations, and the software named SAPTyper was developed. This software provides a convenient and efficient analysis tool for the research and application of forensic proteomic SAP and has important application prospects in individual identification and phenotypic inference based on SAP.

OBJECTIVE: To investigate the application of three-dimensional (3D) reconstruction technology in preoperative planning for anterolateral thigh flap transplantation. METHODS: A retrospective analysis was performed on the clinical data of 11 patients with skin and soft tissue defects treated with free anterolateral thigh flap transplantation between January 2022 and January 2024, who met the selection criteria. There were 8 males and 3 females, aged 34-70 years (mean, 50.8 years). Causes of injury included traffic accidents (4 cases), machine trauma (3 cases), heavy object crush injury (3 cases), and tumor (1 case). The time from injury to flap repair ranged from 7 to 35 days (mean, 23 days). Preoperatively, the patients' CT angiography images were imported into Mimics21.0 software. Through the software's segmentation, editing, and reconstruction functions, 3D visualization and measurement of the vascular pedicle, perforators, wound size, and morphology were performed to plan the flap harvest area, contour, vascular pedicle length, and anastomosis site, guiding the implementation of flap transplantation. RESULTS: The length of the vascular pedicle needed by the recipient site was (9.1±0.9) cm, and the maximum length of vascular pedicle in the donor area was (10.6±0.6) cm, with a significant difference ( t=4.230, P<0.001). The operation time ranged from 220 to 600 minutes (mean, 361.9 minutes). One patient had poor wound healing at the recipient site, which healed after dressing changes. All 11 flaps survived well without necrosis. All patients were followed up 6-19 months (mean, 11 months). Four flaps showed bulkiness and underwent secondary debulking; the remaining flaps had good contour and soft texture. The donor sites healed well, with no sensory disturbance around the incision or complications such as walking impairment. CONCLUSION Preoperative planning using CT angiography data and 3D reconstruction software can effectively determine the flap area, contour, required vascular pedicle length, anastomosis site, and whether vascular grafting is needed, thereby guiding the successful execution of anterolateral thigh flap transplantation.
Humans ; Middle Aged ; Male ; Female ; Adult ; Thigh/diagnostic imaging* ; Aged ; Plastic Surgery Procedures/methods* ; Retrospective Studies ; Imaging, Three-Dimensional/methods* ; Soft Tissue Injuries/surgery* ; Surgical Flaps ; Computed Tomography Angiography ; Free Tissue Flaps/blood supply* ; Preoperative Care

Investigating the correlation between micronucleus formation and male infertility has the potential to improve clinical diagnosis and deepen our understanding of pathological progression. Our study enrolled 2252 male patients whose semen was analyzed from March 2023 to July 2023. Their clinical data, including semen parameters and age, were also collected. Genetic analysis was used to determine whether the sex chromosome involved in male infertility was abnormal (including the increase, deletion, and translocation of the X and Y chromosomes), and subsequent semen analysis was conducted for clinical grouping purposes. The participants were categorized into five groups: normozoospermia, asthenozoospermia, oligozoospermia, oligoasthenozoospermia, and azoospermia. Patients were randomly selected for further study; 41 patients with normozoospermia were included in the control group and 117 patients with non-normozoospermia were included in the study group according to the proportions of all enrolled patients. Cytokinesis-block micronucleus (CBMN) screening was conducted through peripheral blood. Statistical analysis was used to determine the differences in micronuclei (MNi) among the groups and the relationships between MNi and clinical data. There was a significant increase in MNi in infertile men, including those with azoospermia, compared with normozoospermic patients, but there was no significant difference between the genetic and nongenetic groups in azoospermic men. The presence of MNi was associated with sperm concentration, progressive sperm motility, immotile spermatozoa, malformed spermatozoa, total sperm count, and total sperm motility. This study underscores the potential utility of MNi as a diagnostic tool and highlights the need for further research to elucidate the underlying mechanisms of male infertility.
Humans ; Male ; Infertility, Male/genetics* ; Adult ; Micronucleus Tests ; Semen Analysis ; Oligospermia/genetics* ; Azoospermia/genetics* ; Chromosome Aberrations ; Sperm Count ; Micronuclei, Chromosome-Defective ; Middle Aged

OBJECTIVE: To investigate the influencing factors of pathological positive surgical margins (PSM) after radical resection of prostate cancer. METHODS: The clinical data of 407 patients who underwent radical resection of prostate cancer in our hospital from 2011 to 2020 were retrospectively analyzed. And the patients were divided into two groups according to postoperative pathological results. Single factor analysis was used to evaluate the differences in postoperative Gleason score, preoperative total prostate-specific antigen (tPSA), preoperative serum free prostate-specific antigen to preoperative tPSA ratio (fPSA/ tPSA), clinical stage, postoperative pathological stage, operation method, age, body mass index (BMI), diameter and volume of prostate tumor. Multivariate logistic regression was used to determine the independent risk factor of PSM. RESULTS: Among 407 patients with prostate cancer, 179 cases (43.98%) were positive. Univariate analysis showed that there were significant differences in postoperative Gleason score, preoperative tPSA, clinical stage and postoperative pathological stage between the two groups (P<0.05). And Gleason score, preoperative tPSA and pathologic stage were independent risk factors for PSM. CONCLUSION There are relationships between PSM and postoperative Gleason score, tPSA, clinical T stage, postoperative pathologic pT stage. Among them, postoperative Gleason score (Gleason=7 points, Gleason≥8 points), preoperative total prostate-specific antigen (tPSA > 20 μg/L), and postoperative pathologic pT stage (pT3a, pT3b) were independent risk factors for positive pathological margins of prostate cancer.
Margins of Excision ; Prostatic Neoplasms/surgery* ; Prostatectomy/statistics & numerical data* ; Prostate/surgery* ; Retrospective Studies ; Neoplasm Grading/statistics & numerical data* ; Prostate-Specific Antigen/blood* ; Neoplasm Staging/statistics & numerical data* ; Postoperative Period ; Risk Factors ; Humans ; Male