1.Flight fatigue among helicopter flying personnel and contributing factors
Tunan CHEN ; Yan LIU ; Xue YANG ; Baoquan CHENG ; Zhenhao FENG ; Jishu XIAN ; Rui WANG ; Yanchun ZHANG ; Lihua WANG
Chinese Journal of Aerospace Medicine 2025;36(3):167-174
Objective:To investigate the prevalence of flight fatigue among helicopter flying personnel and analyze its contributors in order to provide data for related interventions.Methods:A cross-sectional study was conducted among 404 helicopter flying personnel between October 8, 2021 and July 31, 2022. Data was collected using a self-designed questionnaire, involving the demography of these subjects, sleep-related factors, flight fatigue, perceived causes of fatigue and coping strategies. The Pittsburgh Sleep Quality Index (PSQI), National Aeronautics and Space Administration Task Load Index (NASA-TLX) and Modified Fatigue Impact Scale (MFI-20) were used to assess sleep quality, mental workload, and levels of flight fatigue over the past month. The total scores of MFI-20 were compared across demographic groups, and correlations with PSQI and NASA-TLX scores were analyzed. Multiple linear regression was performed to identify the determinants of flight fatigue.Results:①Demography: among the 404 helicopter flying personnel, 92.8% (375/404) were pilots and 7.2% (29/404) navigators. As for years of service, 41.6% (168/404) served less than 5 years, while 58.4% (236/404) served more than 5 years. 37.9% (153/404) had a family history of insomnia. 18.8% (76/404) did not habitually nap, 68.9% (226/328) napped for ≤30 min, 31.1% (102/328) napped over 30 min, and 18.3% (74/404) had insomnia over the past month. As for helicopter flying personnel, 75.5% (305/404) reported experiencing fatigue, with 69.1% (279/404) attributing it to flight-related factors and 51.5% (208/404) using coffee as a countermeasure.②Scale scores: the total score of PSQI was [5 (3, 7)], while the highest daytime dysfunction score was [1(0, 2)]. The total score of NASA-TLX was [39.19 (26.57, 51.97)], and the effort score was the highest [10.31(5.07, 14.60)]. The total score of MFI-20 averaged (47.28±14.88), with the mental fatigue score being the highest [(10.03±4.42)]. ③Comparisons of MFI-20 total scores: flying personnel with ≤5 years of flying experience had higher MFI-20 total scores than those with >5 years, and those with a family history of insomnia had higher scores than those without ( t=3.35, 2.44, P=0.001, 0.015). Individuals with insomnia over the past month had higher scores than non-insomniacs ( t=3.33, P=0.001). Significant differences in MFI-20 scores were observed based on nap duration ( F=19.95, P<0.001). Non-nappers had higher scores than those napping for ≤30 min ( P=0.005). Flying personnel who napped for >30 min had higher scores than those did not ( P=0.043) or napped for ≤30 min ( P<0.001). ④Correlation analysis: the total score of MFI-20 was positively correlated with sleep quality, sleep latency, sleep disturbances, hypnotic medications, daytime dysfunction, and the total score of PSQI ( r=0.118-0.226, all P<0.05), but negatively with sleep duration ( r=-0.136, P=0.006). The total score of MFI-20 was positively correlated with mental demand, physical demand, and the total score of NASA-TLX ( r=0.119, 0.168, 0.184, P=0.017, 0.001, <0.001). ⑤Multiple linear regression analysis: the determinants of flight fatigue included aircraft types ( B=-4.956, 95% CI:-8.124--1.788), nap duration ( B=3.693, 95% CI: 1.267-6.119), sleep latency ( B=2.371, 95% CI: 0.229-4.513), sleep duration ( B=-7.383, 95% CI:-10.008--4.758), daytime dysfunction ( B=5.003, 95% CI: 2.967-7.039) and physical workload ( B=0.611, 95% CI: 0.324-0.898). Conclusions:Helicopter flying personnel are vulnerable to flight fatigue, which is strongly linked to sleep quality and mental workload. It is crucial to address flying personnel′s self-perceived fatigue, care about fatigue manifestations across aircraft types, and implement targeted interventions to improve sleep quality and reduce mental workload.
2.Flight fatigue among helicopter flying personnel and contributing factors
Tunan CHEN ; Yan LIU ; Xue YANG ; Baoquan CHENG ; Zhenhao FENG ; Jishu XIAN ; Rui WANG ; Yanchun ZHANG ; Lihua WANG
Chinese Journal of Aerospace Medicine 2025;36(3):167-174
Objective:To investigate the prevalence of flight fatigue among helicopter flying personnel and analyze its contributors in order to provide data for related interventions.Methods:A cross-sectional study was conducted among 404 helicopter flying personnel between October 8, 2021 and July 31, 2022. Data was collected using a self-designed questionnaire, involving the demography of these subjects, sleep-related factors, flight fatigue, perceived causes of fatigue and coping strategies. The Pittsburgh Sleep Quality Index (PSQI), National Aeronautics and Space Administration Task Load Index (NASA-TLX) and Modified Fatigue Impact Scale (MFI-20) were used to assess sleep quality, mental workload, and levels of flight fatigue over the past month. The total scores of MFI-20 were compared across demographic groups, and correlations with PSQI and NASA-TLX scores were analyzed. Multiple linear regression was performed to identify the determinants of flight fatigue.Results:①Demography: among the 404 helicopter flying personnel, 92.8% (375/404) were pilots and 7.2% (29/404) navigators. As for years of service, 41.6% (168/404) served less than 5 years, while 58.4% (236/404) served more than 5 years. 37.9% (153/404) had a family history of insomnia. 18.8% (76/404) did not habitually nap, 68.9% (226/328) napped for ≤30 min, 31.1% (102/328) napped over 30 min, and 18.3% (74/404) had insomnia over the past month. As for helicopter flying personnel, 75.5% (305/404) reported experiencing fatigue, with 69.1% (279/404) attributing it to flight-related factors and 51.5% (208/404) using coffee as a countermeasure.②Scale scores: the total score of PSQI was [5 (3, 7)], while the highest daytime dysfunction score was [1(0, 2)]. The total score of NASA-TLX was [39.19 (26.57, 51.97)], and the effort score was the highest [10.31(5.07, 14.60)]. The total score of MFI-20 averaged (47.28±14.88), with the mental fatigue score being the highest [(10.03±4.42)]. ③Comparisons of MFI-20 total scores: flying personnel with ≤5 years of flying experience had higher MFI-20 total scores than those with >5 years, and those with a family history of insomnia had higher scores than those without ( t=3.35, 2.44, P=0.001, 0.015). Individuals with insomnia over the past month had higher scores than non-insomniacs ( t=3.33, P=0.001). Significant differences in MFI-20 scores were observed based on nap duration ( F=19.95, P<0.001). Non-nappers had higher scores than those napping for ≤30 min ( P=0.005). Flying personnel who napped for >30 min had higher scores than those did not ( P=0.043) or napped for ≤30 min ( P<0.001). ④Correlation analysis: the total score of MFI-20 was positively correlated with sleep quality, sleep latency, sleep disturbances, hypnotic medications, daytime dysfunction, and the total score of PSQI ( r=0.118-0.226, all P<0.05), but negatively with sleep duration ( r=-0.136, P=0.006). The total score of MFI-20 was positively correlated with mental demand, physical demand, and the total score of NASA-TLX ( r=0.119, 0.168, 0.184, P=0.017, 0.001, <0.001). ⑤Multiple linear regression analysis: the determinants of flight fatigue included aircraft types ( B=-4.956, 95% CI:-8.124--1.788), nap duration ( B=3.693, 95% CI: 1.267-6.119), sleep latency ( B=2.371, 95% CI: 0.229-4.513), sleep duration ( B=-7.383, 95% CI:-10.008--4.758), daytime dysfunction ( B=5.003, 95% CI: 2.967-7.039) and physical workload ( B=0.611, 95% CI: 0.324-0.898). Conclusions:Helicopter flying personnel are vulnerable to flight fatigue, which is strongly linked to sleep quality and mental workload. It is crucial to address flying personnel′s self-perceived fatigue, care about fatigue manifestations across aircraft types, and implement targeted interventions to improve sleep quality and reduce mental workload.
3.The influence of systemic factors on the prognosis of apical periodontitis
Chinese Journal of Stomatology 2024;59(10):1065-1069
Apical periodontitis (AP) is an inflammatory disease that occurs in the periapical tissue. The treatments of AP mainly include root canal therapy and endodontic surgery which promote the repair of periapical bone tissue by infections clearing and controlling inside or outside the root canal. The evaluation on efficacies of root canal therapy and endodontic surgery is mainly based on clinical and periapical imaging examinations, and the prognosis relates to multiple factors. The systemic factors of patients can directly or indirectly affect the healing of apical periodontitis. The present review summarizes the influence factors, including age, smoking habits, systemic diseases and systemic medication on the prognosis of apical periodontitis treatment, in order to increase the attention of clinicians.
4.Genomic Correlates of Unfavorable Outcome in Locally Advanced Cervical Cancer Treated with Neoadjuvant Chemoradiation
Yuchun WEI ; Chuqing WEI ; Liang CHEN ; Ning LIU ; Qiuxiang OU ; Jiani C. YIN ; Jiaohui PANG ; Zhenhao FANG ; Xue WU ; Xiaonan WANG ; Dianbin MU ; Yang SHAO ; Jinming YU ; Shuanghu YUAN
Cancer Research and Treatment 2022;54(4):1209-1218
Purpose:
Neoadjuvant therapy modality can increase the operability rate and mitigate pathological risks in locally advanced cervical cancer, but treatment response varies widely. It remains unclear whether genetic alterations correlate with the response to neoadjuvant therapy and disease-free survival (DFS) in locally advanced cervical cancer.
Materials and Methods:
A total of 62 locally advanced cervical cancer (stage IB-IIA) patients who received neoadjuvant chemoradiation plus radical hysterectomy were retrospectively analyzed. Patients’ tumor biopsy samples were comprehensively profiled using targeted next generation sequencing. Pathologic response to neoadjuvant treatment and DFS were evaluated against the association with genomic traits.
Results:
Genetic alterations of PIK3CA were most frequent (37%), comparable to that of Caucasian populations from The Cancer Genome Atlas. The mutation frequency of genes including TERT, POLD1, NOS2, and FGFR3 was significantly higher in Chinese patients whereas RPTOR, EGFR, and TP53 were underrepresented in comparison to Caucasians. Germline mutations were identified in 21% (13/62) of the cohort and more than half (57%) had mutations in DNA damage repair genes, including BRCA1/2, TP53 and PALB2. Importantly, high tumor mutation burden, TP53 polymorphism (rs1042522), and KEAP1 mutations were found to be associated with poor pathologic response to neoadjuvant chemoradiation treatment. KEAP1 mutations, PIK3CA-SOX2 co-amplification, TERC copy number gain, and TYMS polymorphism correlated with an increased risk of disease relapse.
Conclusion
We report the genomic profile of locally advanced cervical cancer patients and the distinction between Asian and Caucasian cohorts. Our findings highlight genomic traits associated with unfavorable neoadjuvant chemoradiation response and a higher risk of early disease recurrence.

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