Humans ; Lung Transplantation/adverse effects* ; Risk Factors

Objective: To investigate the association between the distribution of tumor infiltrating lymphocytes (TIL) in EBV associated lymphoepitheliomatoid carcinoma (LELC) and the pathological subtypes of LELC, as well as the clinical significance of TIL distribution. Methods: The LELC patients with sufficient tumor tissues, complete clinical data and positive EBER, who visited Zhejiang Cancer Hospital, Hangzhou, China from January 2006 to October 2018, were selected. Various immunohistochemical markers (CD20, CD138, CD4, CD8, CD56 and FOXP3) were examined for TIL typing. Two pathologists reviewed the hematoxylin and eosin (HE) staining sections and interpreted the immunohistochemical results. Correlation analysis was used to evaluate the relationship between the distribution of TIL subgroups and LELC's pathological characteristics. Survival analyses were conducted to study the prognostic values of TIL subgrouping. Results: A total of 102 patients with EBV related LELC were included. 46 of them were classic LELC (c-LELC) with rich interstitial TIL, and 56 were non-classic LELC (n-LELC) with relatively fewer interstitial TIL. The results of TIL analysis showed that all subtypes of c-LELC were rich in TIL, with B lymphocytes as the dominant subgroup. The number of TIL in n-LELC was fewer than that in c-LELC, with T lymphocytes as the dominant subgroup. There was no significant difference in the distribution of plasma cells between the two groups. Survival analysis showed that the total number of TIL, and the infiltrations of CD20⁺B cells, CD4⁺T cells, and FOXP3⁺Treg cells were associated with better overall survivals (P=0.004, 0.003, 0.008 and 0.025, respectively) and disease-free survivals (P=0.011, 0.003, 0.038 and 0.041, respectively) in patients with LELC. Conclusions: The morphologic subtypes of EBV-related LELC have different tumor immune characteristics. The total number of TIL in the stroma of c-LELC is significantly higher than that of n-LELC. Interestingly, B lymphocytes are the dominant TIL in c-LELC, while T lymphocytes are the dominant TIL in n-LELC. The infiltration of TIL, CD20⁺B cells, CD4⁺T cells and FOXP3⁺Treg cells in LELC may suggest a better prognosis.
Humans ; Lymphocytes, Tumor-Infiltrating ; Herpesvirus 4, Human ; Clinical Relevance ; Prognosis ; Carcinoma, Squamous Cell/pathology* ; Forkhead Transcription Factors

Humans ; B7-H1 Antigen ; Neoplasms/genetics*

Humans ; Adenocarcinoma/pathology* ; Lung/pathology* ; Lung Neoplasms/pathology* ; Neoplasm Invasiveness ; Retrospective Studies

Humans ; Frozen Sections ; Adenoma/diagnosis* ; Bronchial Neoplasms/surgery*

Humans ; Adenocarcinoma of Lung/pathology* ; Adenocarcinoma/pathology* ; Lung Neoplasms/pathology* ; Neoplasm Staging ; Prognosis ; Retrospective Studies ; Adenocarcinoma, Papillary/pathology*

Humans ; Mesothelioma, Malignant/diagnosis* ; Diagnosis, Differential ; Adenocarcinoma/pathology* ; Mesothelioma/pathology* ; Lung Neoplasms/pathology* ; Biomarkers, Tumor ; Pleural Neoplasms/diagnosis* ; Extracellular Matrix Proteins

Objective: To investigate the effect of sugammadex on postoperative nausea and vomiting(PONV) after intracranial aneurysm surgery. Methods: Data from intracranial aneurysms patients who met the inclusion and exclusion criteria and underwent interventional surgery in the Department of Neurosurgery, Peking University International Hospital from January 2020 to March 2021 were prospectively included. According to the random number table method, the patients were divided by 1∶1 into the neostigmine+atropine group (group N) and the sugammadex group (group S). Use an acceleration muscle relaxation monitor for muscle relaxation monitoring, and administer neostigmine+atropine and sugammadex to block residual muscle relaxation drugs after surgery. The incidence rates of PONV and severity, the appearance of anesthesia, and the correlation between PONV and postoperative complications were recorded in both groups during five periods after surgery: 0-0.5 hours (T1),>0.5-2.0 hours(T2),>2.0-6.0 hours (T3),>6.0-12.0 hours (T4) and >12.0-24.0 hours (T5). Group comparisons of quantitative data were performed by the independent sample t-test, and categorical data was performed by the χ² or rank sum test. Results: A total of 66 patients were included in the study, including 37 males and 29 female, aged (59.3±15.4) years (range: 18 to 77 years). The incidence rates of PONV of 33 patients in group S at different time periods of T1, T2, T3, T4, and T5 after surgery were respectively 27.3%(9/33),30.3%(10/33),12.1%(4/33),3.0%(1/33),0(0/33),and the incidence rates of PONV of 33 patients in the group N at different time periods of T1, T2, T3, T4 and T5 after surgery were respectively 36.4%(12/33),36.4%(12/33),33.3%(11/33),6.1%(2/33) and 0(0/33).The incidence of PONV was lower in the group S only in the T3 period after reversal than in the group N (χ²=4.227, P=0.040).However, there was no statistically significant difference in the incidence of PONV between the two groups of patients in other periods (all P>0.05). The recovery time for spontaneous breathing in patients in group S was (7.7±1.4) minutes, the extubation time was (12.4±5.3) minutes, and the safe exit time for anesthesia recovery was (12.3±3.4) minutes; the N groups were (13.9±2.0) minutes, (18.2±6.0) minutes, and (18.6±5.2) minutes, respectively; three time periods in group S were shorter than those in group N, and the differences were statistically significant (all P<0.05). The results regarding the occurrence of complications in patients with different levels of PONV at different time intervals after surgery in the two groups were as follows: in the T3 time period of group N, a significant difference was observed only in the occurrence of postoperative complications among patients with different levels of PONV (χ²=24.786, P<0.01). However, in the T4 time period, significant differences were found in the occurrence of postoperative complications among both the same level and different level PONV patients (χ²=15.435, 15.435, both P<0.01). Significant differences were also observed in the occurrence of postoperative complications among the same level and different level PONV patients in both the T3 and T4 time periods of group S (all P<0.01). Conclusion: Sugammadex can be used to reverse muscle relaxation in patients undergoing intracranial aneurysm intervention surgery,and it does not have a significant impact on the incidence of PONV, it can also optimize the quality of anesthesia recovery and reduce the incidence of complications after intracranial aneurysm embolization surgery.
Male ; Humans ; Female ; Sugammadex ; Postoperative Nausea and Vomiting/chemically induced* ; Neostigmine/adverse effects* ; Intracranial Aneurysm/surgery* ; gamma-Cyclodextrins/adverse effects* ; Atropine

Background: and Purpose Recent studies suggested an increased incidence of cerebral venous thrombosis (CVT) during the coronavirus disease 2019 (COVID-19) pandemic. We evaluated the volume of CVT hospitalization and in-hospital mortality during the 1st year of the COVID-19 pandemic compared to the preceding year. Methods: We conducted a cross-sectional retrospective study of 171 stroke centers from 49 countries. We recorded COVID-19 admission volumes, CVT hospitalization, and CVT in-hospital mortality from January 1, 2019, to May 31, 2021. CVT diagnoses were identified by International Classification of Disease-10 (ICD-10) codes or stroke databases. We additionally sought to compare the same metrics in the first 5 months of 2021 compared to the corresponding months in 2019 and 2020 (ClinicalTrials.gov Identifier: NCT04934020). Results: There were 2,313 CVT admissions across the 1-year pre-pandemic (2019) and pandemic year (2020); no differences in CVT volume or CVT mortality were observed. During the first 5 months of 2021, there was an increase in CVT volumes compared to 2019 (27.5%; 95% confidence interval [CI], 24.2 to 32.0; P<0.0001) and 2020 (41.4%; 95% CI, 37.0 to 46.0; P<0.0001). A COVID-19 diagnosis was present in 7.6% (132/1,738) of CVT hospitalizations. CVT was present in 0.04% (103/292,080) of COVID-19 hospitalizations. During the first pandemic year, CVT mortality was higher in patients who were COVID positive compared to COVID negative patients (8/53 [15.0%] vs. 41/910 [4.5%], P=0.004). There was an increase in CVT mortality during the first 5 months of pandemic years 2020 and 2021 compared to the first 5 months of the pre-pandemic year 2019 (2019 vs. 2020: 2.26% vs. 4.74%, P=0.05; 2019 vs. 2021: 2.26% vs. 4.99%, P=0.03). In the first 5 months of 2021, there were 26 cases of vaccine-induced immune thrombotic thrombocytopenia (VITT), resulting in six deaths. Conclusions During the 1st year of the COVID-19 pandemic, CVT hospitalization volume and CVT in-hospital mortality did not change compared to the prior year. COVID-19 diagnosis was associated with higher CVT in-hospital mortality. During the first 5 months of 2021, there was an increase in CVT hospitalization volume and increase in CVT-related mortality, partially attributable to VITT.

Objective: This study evaluated the validity of self-reported smartphone usage data against objectively-measured smartphone usage data by directly tracking the activities in the participants’ smartphone among Chinese adolescents and young adults in Hong Kong. Methods: A total of 187 participants were recruited (mean age 19.4, 71.7% female) between 2017 and 2018. A smartphone usage tracking app was installed on all participants’ smartphone for 7 consecutive days. After the 7-day monitoring period, they completed a selfadministered questionnaire on smartphone usage habits. Results: Although the correlation between self-reported and objectively-measured total smartphone usage time was insignificant (ρ=-0.10, p=0.18), in three out of the four usage domains were positively and significantly correlated, namely social network (ρ=0.21, p=0.005), instant messaging (ρ=0.27, p<0.001), and games (ρ=0.64, p<0.001). Participants’ self-report of the total time spent on smartphones exceeded the objective data by around 760 min per week (self-reported 1,930.3 min/wk vs. objectively-measured 1,170.7 min/wk, p<0.001). Most of the over-reporting was contributed by the web browsing domain (self-reported 447.8 min/wk vs. objectively-measured 33.3 min/wk, p<0.001). Conclusion Our results showed large discrepancies between self-reported smartphone and objectively-measured smartphone usage except for self-reported usage on game apps.