Objective: Executive function correlates with the parasympathetic nervous system (PNS) based on static heart rate variability (HRV) measurements. Our study advances this understanding by employing dynamic assessments of the PNS to explore and quantify its relationship with inhibitory control (IC). Methods: We recruited 31 men aged 20–35 years. We monitored their electrocardiogram (ECG) signals during the administration of the Conners’ Continuous Performance Test-II (CCPT-II) on a weekly basis over 2 weeks. HRV analysis was performed on ECG-derived RR intervals using 5-minute windows, each overlapping for the next 4 minutes to establish 1-minute intervals. For each time window, the HRV metrics extracted were: mean RR intervals, standard deviation of NN intervals (SDNN), low-frequency power with logarithm (lnLF), and high-frequency power with logarithm (lnHF). Each value was correlated with detectability and compared to the corresponding baseline value at t0. Results: Compared with the baseline level, SDNN and lnLF showed marked decreases during CCPT-II. The mean values of HRV showed significant correlation with d’, including mean SDNN (R=0.474, p=0.012), mean lnLF (R=0.390, p=0.045), and mean lnHF (R=0.400, p=0.032). In the 14th time window, the significant correlations included SDNN (R=0.578, p=0.002), lnLF (R=0.493, p=0.012), and lnHF (R=0.432, p=0.031). Significant correlation between d’ and HRV parameters emerged only during the initial CCPT-II. Conclusion A significant correlation between PNS and IC was observed in the first session alone. The IC in the repeated CCPT-II needs to consider the broader neural network.

Objective: Executive function correlates with the parasympathetic nervous system (PNS) based on static heart rate variability (HRV) measurements. Our study advances this understanding by employing dynamic assessments of the PNS to explore and quantify its relationship with inhibitory control (IC). Methods: We recruited 31 men aged 20–35 years. We monitored their electrocardiogram (ECG) signals during the administration of the Conners’ Continuous Performance Test-II (CCPT-II) on a weekly basis over 2 weeks. HRV analysis was performed on ECG-derived RR intervals using 5-minute windows, each overlapping for the next 4 minutes to establish 1-minute intervals. For each time window, the HRV metrics extracted were: mean RR intervals, standard deviation of NN intervals (SDNN), low-frequency power with logarithm (lnLF), and high-frequency power with logarithm (lnHF). Each value was correlated with detectability and compared to the corresponding baseline value at t0. Results: Compared with the baseline level, SDNN and lnLF showed marked decreases during CCPT-II. The mean values of HRV showed significant correlation with d’, including mean SDNN (R=0.474, p=0.012), mean lnLF (R=0.390, p=0.045), and mean lnHF (R=0.400, p=0.032). In the 14th time window, the significant correlations included SDNN (R=0.578, p=0.002), lnLF (R=0.493, p=0.012), and lnHF (R=0.432, p=0.031). Significant correlation between d’ and HRV parameters emerged only during the initial CCPT-II. Conclusion A significant correlation between PNS and IC was observed in the first session alone. The IC in the repeated CCPT-II needs to consider the broader neural network.

Objective: Executive function correlates with the parasympathetic nervous system (PNS) based on static heart rate variability (HRV) measurements. Our study advances this understanding by employing dynamic assessments of the PNS to explore and quantify its relationship with inhibitory control (IC). Methods: We recruited 31 men aged 20–35 years. We monitored their electrocardiogram (ECG) signals during the administration of the Conners’ Continuous Performance Test-II (CCPT-II) on a weekly basis over 2 weeks. HRV analysis was performed on ECG-derived RR intervals using 5-minute windows, each overlapping for the next 4 minutes to establish 1-minute intervals. For each time window, the HRV metrics extracted were: mean RR intervals, standard deviation of NN intervals (SDNN), low-frequency power with logarithm (lnLF), and high-frequency power with logarithm (lnHF). Each value was correlated with detectability and compared to the corresponding baseline value at t0. Results: Compared with the baseline level, SDNN and lnLF showed marked decreases during CCPT-II. The mean values of HRV showed significant correlation with d’, including mean SDNN (R=0.474, p=0.012), mean lnLF (R=0.390, p=0.045), and mean lnHF (R=0.400, p=0.032). In the 14th time window, the significant correlations included SDNN (R=0.578, p=0.002), lnLF (R=0.493, p=0.012), and lnHF (R=0.432, p=0.031). Significant correlation between d’ and HRV parameters emerged only during the initial CCPT-II. Conclusion A significant correlation between PNS and IC was observed in the first session alone. The IC in the repeated CCPT-II needs to consider the broader neural network.

Objective: Executive function correlates with the parasympathetic nervous system (PNS) based on static heart rate variability (HRV) measurements. Our study advances this understanding by employing dynamic assessments of the PNS to explore and quantify its relationship with inhibitory control (IC). Methods: We recruited 31 men aged 20–35 years. We monitored their electrocardiogram (ECG) signals during the administration of the Conners’ Continuous Performance Test-II (CCPT-II) on a weekly basis over 2 weeks. HRV analysis was performed on ECG-derived RR intervals using 5-minute windows, each overlapping for the next 4 minutes to establish 1-minute intervals. For each time window, the HRV metrics extracted were: mean RR intervals, standard deviation of NN intervals (SDNN), low-frequency power with logarithm (lnLF), and high-frequency power with logarithm (lnHF). Each value was correlated with detectability and compared to the corresponding baseline value at t0. Results: Compared with the baseline level, SDNN and lnLF showed marked decreases during CCPT-II. The mean values of HRV showed significant correlation with d’, including mean SDNN (R=0.474, p=0.012), mean lnLF (R=0.390, p=0.045), and mean lnHF (R=0.400, p=0.032). In the 14th time window, the significant correlations included SDNN (R=0.578, p=0.002), lnLF (R=0.493, p=0.012), and lnHF (R=0.432, p=0.031). Significant correlation between d’ and HRV parameters emerged only during the initial CCPT-II. Conclusion A significant correlation between PNS and IC was observed in the first session alone. The IC in the repeated CCPT-II needs to consider the broader neural network.

Objective: Executive function correlates with the parasympathetic nervous system (PNS) based on static heart rate variability (HRV) measurements. Our study advances this understanding by employing dynamic assessments of the PNS to explore and quantify its relationship with inhibitory control (IC). Methods: We recruited 31 men aged 20–35 years. We monitored their electrocardiogram (ECG) signals during the administration of the Conners’ Continuous Performance Test-II (CCPT-II) on a weekly basis over 2 weeks. HRV analysis was performed on ECG-derived RR intervals using 5-minute windows, each overlapping for the next 4 minutes to establish 1-minute intervals. For each time window, the HRV metrics extracted were: mean RR intervals, standard deviation of NN intervals (SDNN), low-frequency power with logarithm (lnLF), and high-frequency power with logarithm (lnHF). Each value was correlated with detectability and compared to the corresponding baseline value at t0. Results: Compared with the baseline level, SDNN and lnLF showed marked decreases during CCPT-II. The mean values of HRV showed significant correlation with d’, including mean SDNN (R=0.474, p=0.012), mean lnLF (R=0.390, p=0.045), and mean lnHF (R=0.400, p=0.032). In the 14th time window, the significant correlations included SDNN (R=0.578, p=0.002), lnLF (R=0.493, p=0.012), and lnHF (R=0.432, p=0.031). Significant correlation between d’ and HRV parameters emerged only during the initial CCPT-II. Conclusion A significant correlation between PNS and IC was observed in the first session alone. The IC in the repeated CCPT-II needs to consider the broader neural network.

Radical gastrectomy with D2 lymphadenectomy has been widely performed as the standard surgery for patients with gastric cancer in major medical centers in China and abroad. However, the exact extent of lymph node dissection is still controversial. In the latest version of the Japanese Gastric Cancer Treatment Guidelines, No. 14v lymph nodes (along the root of the superior mesenteric vein) are again defined as loco-regional lymph nodes, and it is clarified that distal gastric cancer presenting with infra-pyloric regional lymph node (No.6) metastasis is recommended for D2+ superior mesenteric vein (No. 14v) lymph node dissection. To explore the relevance and clinical significance of No.6 and No.14v lymphadenectomy in radical gastric cancer surgery, a review of the national and international literature revealed that No.6 lymph node metastasis was associated with No.14v lymph node metastasis, that No.6 lymph node status was a valid predictor of No.14v lymph node negative status and false negative rate, and that for gastric cancer patients with No. 14v lymph node negative and No.6 lymph node positive, the dissection of No.14v lymph node may also have some significance. The addition of No. 14v lymph node dissection in radical gastrectomy is safe, but it is more important to distinguish the patients who can benefit from it. Professor Liang Han of Tianjin Medical University Cancer Hospital is currently leading a multicenter, large-sample, prospective clinical trial (NCT02272894) in China, which is expected to provide higher level evidence for the clinical significance of lymph node dissection in No.14v.
Humans ; Stomach Neoplasms/pathology* ; Lymphatic Metastasis/pathology* ; Prospective Studies ; Retrospective Studies ; Lymph Nodes/pathology* ; Lymph Node Excision ; Gastrectomy ; Multicenter Studies as Topic

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 ; Lipoma/pathology* ; Immunohistochemistry

Objective: To explore the application of manual screening collaborated with the Artificial Intelligence TPS-Assisted Cytologic Screening System in urinary exfoliative cytology and its clinical values. Methods: A total of 3 033 urine exfoliated cytology samples were collected at the Henan People's Hospital, Capital Medical University, Beijing, China. Liquid-based thin-layer cytology was prepared. The slides were manually read under the microscope and digitally presented using a scanner. The intelligent identification and analysis were carried out using an artificial intelligence TPS assisted screening system. The Paris Report Classification System of Urinary Exfoliated Cytology 2022 was used as the evaluation standard. Atypical urothelial cells and even higher grade lesions were considered as positive when evaluating the recognition sensitivity, specificity, and diagnostic accuracy of artificial intelligence-assisted screening systems and human-machine collaborative cytologic screening methods in urine exfoliative cytology. Among the collected cases, there were also 1 100 pathological tissue controls. Results: The accuracy, sensitivity and specificity of the AI-assisted cytologic screening system were 77.18%, 90.79% and 69.49%; those of human-machine coordination method were 92.89%, 99.63% and 89.09%, respectively. Compared with the histopathological results, the accuracy, sensitivity and specificity of manual reading were 79.82%, 74.20% and 95.80%, respectively, while those of AI-assisted cytologic screening system were 93.45%, 93.73% and 92.66%, respectively. The accuracy, sensitivity and specificity of human-machine coordination method were 95.36%, 95.21% and 95.80%, respectively. Both cytological and histological controls showed that human-machine coordination review method had higher diagnostic accuracy and sensitivity, and lower false negative rates. Conclusions: The artificial intelligence TPS assisted cytologic screening system has achieved acceptable accuracy in urine exfoliation cytologic screening. The combination of manual screening and artificial intelligence TPS assisted screening system can effectively improve the sensitivity and accuracy of cytologic screening and reduce the risk of misdiagnosis.
Humans ; Artificial Intelligence ; Urothelium/pathology* ; Cytodiagnosis ; Epithelial Cells/pathology* ; Sensitivity and Specificity ; Urologic Neoplasms/urine*

We developed and assessed the performance of a new multiplex real-time PCR assay for the detection of all Chlamydia species and simultaneous differentiation of Chlamydia psittaci and Chlamydia pneumoniae—two important human respiratory pathogens—in human clinical specimens. Next-generation sequencing was used to identify unique targets to design real-time PCR assays targeting all Chlamydia species, C. psittaci, and C. pneumoniae. To validate the assay, we used a panel of 49 culture isolates comprising seven C. psittaci genotypes, eight C. pneumoniae isolates, seven other Chlamydia species, and 22 near-neighbor bacterial and viral isolates, along with 22 specimens from external quality assessment (EQA) panels and 34 nasopharyngeal and oropharyngeal swabs and cerebrospinal fluid, stool, and sputum specimens previously identified as positive or negative for C. psittaci or C. pneumoniae. The assays were 100% specific, with limits of detection of 7.64– 9.02 fg/μL. The assay results matched with historical assay results for all specimens, except for one owing to the increased sensitivity of the new C. psittaci assay; the results of the EQA specimens were 100% accurate. This assay may improve the timely and accurate clinical diagnosis of Chlamydia infections and provide a greater understanding of the burden of disease caused by these agents.