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.

[摘 要] 目的：基于生物信息学分析和体内、体外实验研究长链非编码RNA00511（LINC00511）敲减对非小细胞肺癌细胞增殖、凋亡、侵袭等恶性生物学行为的影响，并初步探究其作用机制。方法：通过基因表达谱交互分析（GEPIA）数据库分析LINC00511在非小细胞肺癌的表达水平，及其与患者肿瘤分期、生存期等临床特征、肿瘤细胞恶性生物学行为有关基因的相关性；利用shRNA慢病毒载体构建LINC00511敲减的H1299肺癌细胞株，克隆形成实验、划痕愈合实验和流式细胞术分别检测对H1299细胞增殖、迁移、细胞周期和凋亡能力的影响，qRT-PCR检测相关调控基因表达，WB法检测肿瘤相关蛋白的表达；构建裸鼠皮下移植瘤模型，取瘤组织进行免疫组织化学实验检测Ki67表达情况。结果：GEPIA数据库分析表明LINC00511在非小细胞肺癌组织中表达水平升高，且与该病的临床分期情况相关（P < 0.05），LINC00511与肺癌中CASP3、CCNB1、CDK4等多种基因表达均有相关性（P < 0.01）；LINC00511敲减可抑制细胞的克隆形成和迁移能力、促进肺癌细胞凋亡并影响细胞周期进展（P < 0.05，P < 0.01）；LINC00511敲减可下调肺癌细胞CCNB、CDK4、TGF-β1基因的表达（P < 0.01），对CCND1、VEGFA基因表达无明显影响，LINC00511敲减可抑制细胞内MMP9、CTNNB1表达，上调CASP3的表达（P < 0.05，P < 0.01）；裸鼠体内实验证实，LINC00511敲减可抑制移植瘤体组织内Ki67的表达（P < 0.01）。结论：LINC00511在非小细胞肺癌组织中呈高表达，与肺癌临床分期和多种基因表达具有相关性，LINC00511敲减可能通过影响相关基因、蛋白的表达，抑制肺癌H1299细胞的恶性生物学行为。

[摘 要] 目的：探讨精氨酸-甘氨酸-天冬氨酸（RGD）修饰对肿瘤抑素19肽（T-19）抗肝癌活性的影响，比较分析T-19及RGD修饰的T-19（RGD-T-19）对肝癌SK-Hep-1细胞增殖、侵袭和迁移能力的影响。方法：用Fmoc固相法合成T-19及RGD-T-19，用高效液相色谱仪和质谱进行分离、鉴定。常规培养SK-Hep-1细胞，用0、50、100、150、200、250 mg/mL的T-19及RGD-T-19分别处理细胞，分为0 mg/mL（对照）组、50 mg/mL组、100 mg/mL组、150 mg/mL组、200 mg/mL组、250 mg/mL组。CCK-8法、克隆形成实验、划痕愈合实验和Tanswell小室实验、WB法和qPCR法分别检测SK-Hep-1细胞的增殖、迁移、侵袭能力，以及环氧合酶-2（COX-2）、基质金属蛋白酶-2（MMP-2）、MMP-9、组织基质金属蛋白酶抑制剂-1（TIMP-1）、TIMP-2蛋白和MMP-1、MMP-2 mRNA的表达。结果：经质谱鉴定，用Fmoc固相法合成的T-19及RGD-T-19纯度高。T-19和RGD-T-19均能显著抑制SK-Hep-1细胞的增殖、迁移、侵袭能力，抑制COX-2蛋白、MMP-2和MMP-9蛋白及mRNA的表达、促进TIMP-1、TIMP-2蛋白的表达（P < 0.05, P < 0.01, P < 0.001），RGD-T-19的抑制或促进效应均明显强于T-19（均P < 0.05）。结论：利用Fmoc固相法合成了纯度高、活性好的T-19及RGD-T-19，两种肽均能抑制SK-Hep-1细胞增殖、侵袭和迁移能力，RGD-T-19作用明显强于T-19。

[摘 要] 目的：探究野生型水疱性口炎病毒印第安纳株（VSV-IN）对小鼠三阴性乳腺癌4T1细胞移植模型小鼠的免疫调节及肿瘤转移的影响。方法：VSV以MOI=1、MOI=10、MOI=100感染4T1细胞12、24、48 h后，CCK-8法检测4T1细胞死亡率，划痕愈合实验检测细胞迁移能力，qPCR检测细胞中E-cadherin、MMP-2、MMP-9 mRNA的表达。于雌性BALB/c小鼠脂肪垫接种1×106个/mL的4T1细胞0.1 mL，构建4T1细胞荷瘤小鼠模型，待小鼠肿瘤体积达200 mm3，分别向移植瘤内注射PBS、紫杉醇（TAX）（15 mg/kg）、VSV-IN（1×106 pfu/只），每周1次。给药4次后，处死小鼠、剥离完整移植瘤组织，测量肿瘤体积及质量，肺组织病理切片经H-E染色后观察肿瘤肺部转移结节，流式细胞术检测脾组织中T细胞亚群比例，ELISA法检测小鼠血清IL-6及TNF-α水平，利用GEPIA在线分析乳腺肿中迁移相关蛋白mRNA的表达，免疫组化法检测肿瘤中MMP-2、MMP-9与E-cadherin的表达，利用蛋白-蛋白对接技术预测VSV-IN的G蛋白、M蛋白与ERK2、E-cadherin的亲和力。结果：经MOI=10、100的VSV-IN处理48 h后，4T1细胞死亡率显著高于对照组（均P<0.01）；与对照组相比，VSV-IN组（MOI=10）细胞迁移率明显降低（P<0.01），MMP-9 mRNA的相对表达量明显降低（P<0.05）；与对照组小鼠相比，VSV-IN组移植瘤生长较对照组减缓且终点体积显著减小（P<0.05），VSV-IN组小鼠肺转移结节数量显著减少[（12.86±1.86） vs （24±3.67）个，P<0.01]，脾内CD4+ T、CD8+ T细胞比例显著升高（均P<0.05），血清TNF-α、IL-6含量显著升高（均P<0.01）；GEPIA分析发现在乳腺癌中E-cadherin、MMP-9表达水平均高于癌旁组织（P<0.05）；VSV-IN组小鼠肿瘤细胞内MMP-9表达明显低于对照组（P<0.05）；VSV-IN的G、M蛋白与ERK2的结合自由能分别为–11.7 kcal/mol、–6.4 kcal/mol。结论：野生型VSV-IN可抑制4T1细胞荷瘤小鼠的移植瘤生长及转移，这可能与其促进抗肿瘤免疫及调控迁移相关蛋白表达有关。

[摘 要] 目的：探讨补肾健脾方（BSJP）介导法尼醇X受体（FXR）抑制肝癌细胞AH-130诱导的癌性恶病质（CC）大鼠模型的作用及其机制。方法：腹腔注射AH-130细胞建立肝癌CC大鼠模型，实验分为空白对照组、模型对照组、FXR激动剂（CDCA）组、BSJP组和BSJP + CDCA组。建模后，用CDCA、BSJP连续治疗大鼠16 d，每周称量大鼠体质量。实验结束时开腹，取腹主动脉血、粪便及附睾、腹股沟和肩胛区棕色脂肪质量。采用液相色谱-质谱法（LC-MS）检测大鼠血清和粪便中胆汁酸组分及含量，WB、qPCR法检测大鼠空肠、棕色及白色脂肪组织中FXR、Wnt家族成员10b（Wnt10b）、β-连环蛋白（β-catenin）、解偶联蛋白1（UCP-1）的表达。结果：与空白对照组相比，模型对照组大鼠体质量明显降低（P < 0.01）；与模型对照组相比，CDCA、BSJP、BSJP + CDCA组大鼠体质量均增加（均P < 0.01）。与空白对照组相比，模型对照组附睾、腹股沟和肩胛区域及总棕色脂肪质量均上升（均P < 0.05）；与模型对照组相比，各治疗组大鼠附睾、腹股沟区、棕色脂肪质量均下降（均P < 0.05），而肩胛区棕色脂肪组织质量下降无差异（P > 0.05）；各治疗组总棕色脂肪质量均显著下降（P < 0.05或P < 0.01）。LC-MS分析显示，各组大鼠血清及粪便中胆汁酸组成及含量均发生改变。qPCR、WB法结果证实，与模型组相比，BSJP和BSJP + CDCA可促进大鼠回肠、棕色脂肪及白色脂肪组织中FXR mRNA和蛋白表达升高（均P < 0.05），Wnt10b、β-catenin、UCP-1 mRNA和蛋白表达均下降（均P < 0.05）。结论：BSJP能够抑制肝癌AH-130细胞诱导的大鼠CC，并减轻由此引起的体质量下降和棕色脂肪组织的形成，其机制可能涉及调控FXR并通过抑制棕色脂肪中与Wnt通路相关的Wnt10b、β-catenin和UCP-1的表达来实现。

[摘 要] 目的：构建负载二氧化锰（MnO2）纳米颗粒的可得然（Cur）复合水凝胶MnO2@Cur（简称MGel），研究其对黑色素瘤B16-F10细胞的杀伤效果。方法：采用热诱导法制备Cur水凝胶（Gel），物理负载MnO2构建MGel，表征其宏观和微观形貌，检测其机械性能、降解性能以及光热转换性能等理化性能，并研究其联合PTT对小鼠皮肤黑色素瘤B16-F10细胞的光热杀伤效果。结果：MGel具有优异的机械和可降解性能，抗拉伸强度达（127.97±3.60）kPa、抗压缩强度达（151.44±5.23）kPa，28 d降解率约58.17%。MGel负载MnO2纳米片（粒径约180 nm）获得优异的光热转换性能，负载1.0 mg/mL MnO2的MGel在1.0 W/cm2的808 nm NIR光照4 min后到达最高温度50 ℃。细胞毒性实验和Calcein-AM/PI荧光双染色实验表明，MGel联合PTT有效杀伤B16-F10黑色素瘤细胞，NIR光照使得MGel组细胞存活率降低至（4.68±0.66）%（P<0.000 1）。结论：MGel复合水凝胶具备优异的机械性能、可降解性能以及光热转换性能，其联合PTT能有效杀伤肿瘤细胞，可能成为一种有效治疗黑色素瘤的新手段。