Stratified Prognostic Comparison Between Stage IIB-IVA Cervical Adenocarcinoma and Squamous Cell Carcinoma: A SEER Database-Based Study.

Objective: In current most observational studies, the prognosis of cervical adenocarcinoma is worse than that of cervical squamous cell carcinoma. However, most of the current studies are holistic and lack more detailed staging and grouping analysis of the prognosis of the two types of cervical tumors. Patients and Methods: Inclusion from the SEER database of stage IIB-IVA cervical squamous cell carcinoma and cervical adenocarcinoma patients who did not undergo surgery from 2000 to 2019, underwent radiotherapy/chemotherapy/radiotherapy and chemotherapy/no treatment, and then propensity score matching (PSM) was performed to eliminate confounding factors between cervical squamous cell carcinoma and cervical adenocarcinoma patients with the same stage and treatment method. After matching the original data and propensity score, logarithmic rank test and chi square test were used to evaluate the survival benefits of different stages and treatment methods for patients using Kaplan Meier curve. The prognosis of two types of cervical tumors under the same treatment method was compared, and factors that may cause poor prognosis were analyzed, excluding confounding factors. Results: A total of 10,057 patients were included in this study, and survival analysis showed a significant correlation between the treatment method used and patient prognosis (P<0.05). However, for patients who received radiotherapy or no special treatment, OS and CSS were only related to tumor stage and not to tumor type. In patients undergoing radiotherapy and chemotherapy, the OS and CSS of stage IIIA and IVA patients are not related to tumor pathological characteristics, while the OS of stage IIB patients is not related to tumor properties after PSM. Conclusion: In patients undergoing radiotherapy and chemotherapy, the OS and CSS of stage IIIA and IVA patients were not related to histological type, while the OS of stage IIB patients was not related to histological type after PSM.

Characterization of Cancer Cell Mechanics by Measuring Active Deformation Behavior.

Active deformation behavior reflects cell structural dynamics adapting to varying environmental constraints during malignancy progression. In most cases, cell mechanics is characterized by modeling using static equilibrium systems, which fails to comprehend cell deformation behavior leading to inaccuracies in distinguishing cancer cells from normal cells. Here, a method is introduced to measure the active deformation behavior of cancer cells using atomic force microscopy (AFM) and the newly developed deformation behavior cytometry (DBC). During the measurement, cells are deformed and allows a long timescale relaxation (≈5 s). Two parameters are derived to represent deformation behavior: apparent Poisson's ratio for adherent cells, which is measured with AFM and refers to the ratio of the lateral strain to the longitudinal strain of the cell, and shape recovery for suspended cells, which is measured with DBC. Active deformation behavior defines cancer cell mechanics better than traditional mechanical parameters (e.g., stiffness, diffusion, and viscosity). Additionally, aquaporins are essential for promoting the deformation behavior, while the actin cytoskeleton acts as a downstream effector. Therefore, the potential application of the cancer cell active deformation behavior as a biomechanical marker or therapeutic target in cancer treatment should be evaluated.

The Effect of Cervical Cold-Knife Conization (CKC) on HPV Infection in Patients with High-Grade Cervical Intraepithelial Neoplasia: A Retrospective Study.

Purpose: Investigation of HPV infection treatment in women undergoing cervical cold-knife conization for advanced cervical intraepithelial neoplasia. Patients and Methods: A retrospective analysis was conducted on patients who underwent cervical cold-knife conization for cervical intraepithelial neoplasia grade II-III at Beijing Obstetrics and Gynecology Hospital from January 2017 to December 2018. The HPV infection status of the patients at 6 months, 1 year, and 2 years after surgery was collected. We use chi square analysis and binary logistic regression to evaluate various factors such as age, number of pregnancies, number of cesarean sections, number of vaginal deliveries, HPV type, size of surgical specimens (diameter and height), and the influence of specimen edge on HPV infection. Results: A total of 334 patients were included in the analysis. The patients are mainly infected with HPV 16/58/52. Age is a influencing factor for HPV recovery 12 months after CKC surgery (P=0.002). Based on the diagnosis of HPV one year after CKC, the recovery rate of HPV58 patients is significantly lower than HPV16. Age is a influencing factor for the recovery of HPV infection (P<0.05). Conclusion: The treatment of HPV infection by CKC is related to the patient's age and HPV subtype but not to number of pregnancies, number of pregnancies, number of vaginal deliveries, size of surgical specimens, and marginal conditions. The rate of HPV negative conversion is relatively high 24 months after the patient does not undergo surgery, but there is currently a lack of data on cervical lesions that match HPV results.

Identifying Intraoperative Spinal Cord Injury Location from Somatosensory Evoked Potentials' Time-Frequency Components.

Excessive distraction in corrective spine surgery can lead to iatrogenic distraction spinal cord injury. Diagnosis of the location of the spinal cord injury helps in early removal of the injury source. The time-frequency components of the somatosensory evoked potential have been reported to provide information on the location of spinal cord injury, but most studies have focused on contusion injuries of the cervical spine. In this study, we established 19 rat models of distraction spinal cord injury at different levels and collected the somatosensory evoked potentials of the hindlimb and extracted their time-frequency components. Subsequently, we used k-medoid clustering and naive Bayes to classify spinal cord injury at the C5 and C6 level, as well as spinal cord injury at the cervical, thoracic, and lumbar spine, respectively. The results showed that there was a significant delay in the latency of the time-frequency components distributed between 15 and 30 ms and 50 and 150 Hz in all spinal cord injury groups. The overall classification accuracy was 88.28% and 84.87%. The results demonstrate that the k-medoid clustering and naive Bayes methods are capable of extracting the time-frequency component information depending on the spinal cord injury location and suggest that the somatosensory evoked potential has the potential to diagnose the location of a spinal cord injury.

A risk prediction nomogram of endometrial carcinoma and precancerous lesions in postmenopausal women: A retrospective study.

This study aimed to develop a risk prediction nomogram for endometrial carcinoma and precancerous lesions in postmenopausal women to provide postmenopausal patients with more information on disease probability, work out personalized medical plans, and reduce unnecessary invasive clinical examinations. We enrolled 340 patients who underwent hysteroscopy at Beijing Maternity Hospital between March 2016 and July 2018. The patients were divided into the low-risk (275 patients) and high-risk (65 patients) groups, according to the results of the pathological examinations. Binary logistic analysis was performed to evaluate the 20 potential risk factors for endometrial cancer and precancerous lesions in postmenopausal women and to screen for certain risk factors using the Statistical Package for the Social Sciences version 26.0. Using R 4.0.3, we built a prediction nomogram that incorporated the selected factors. The discrimination, calibration, and clinical usefulness of the prediction model were assessed using the concordance (C)-index, calibration plot, and decision curve analysis. Internal validation was assessed using bootstrapping validation. Predictors included in the prediction nomogram included obesity, vaginal bleeding, family history of gynecological malignancies, endometrial thickness ≥ 1.15 cm, and color Doppler flow imaging blood flow. The model displayed good discrimination, with a C-index of 0.853, and good calibration. Decision curve analysis showed that the model was clinically useful, with a benefit range of 2% to 93%. A high C-index value of 0.844 could still be reached in the interval validation. Obesity, vaginal bleeding, family history of gynecological malignancies, endometrial thickness ≥ 1.15 cm, and color Doppler flow imaging blood flow were independent risk factors for endometrial cancer and precancerous lesions. Thus, the prediction nomogram can be conveniently used to facilitate individual risk prediction in patients with endometrial cancer and precancerous lesions.