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1.
Med Sci Monit ; 27: e931881, 2021 Jun 12.
Article in English | MEDLINE | ID: mdl-34117207

ABSTRACT

BACKGROUND The coronavirus disease 2019 (COVID-19) outbreak has exerted immense pressure on medical systems in China and abroad. This study aimed to compare the sleep quality of medical personnel conscripted to the Wuhan Union Cancer Centre to offer support during the early stages of the COVID-19 pandemic to the sleep quality of those who remained at Anhui Medical University Hospital and to determine the role of interventions in improving sleep quality. MATERIAL AND METHODS Questionnaires were completed by 369 individuals who were conscripted to support Wuhan (N=137) and others who were not (the control group; N=232). The Pittsburgh Sleep Quality Index (PSQI) was used to measure the duration and quality of sleep. The Anhui Provincial Health Commission organized a comprehensive intervention, consisting of physical-psychological-social dimensions, over the course of 2 weeks. RESULTS Only 34.21% of the Wuhan support workers reported better sleep quality, as opposed to the 55.60% of the control group at stage 1 (t/χ²=14.005, P<.001). Furthermore, despite the Wuhan support group being more prone to poor sleep quality, their sleep quality significantly improved after the interventions. CONCLUSIONS The findings from this study showed that medical staff who were conscripted to offer support during the early stages of the COVID-19 pandemic suffered from impaired quality of sleep. The use of questionnaire-based sleep assessments may provide individualized approaches to supporting medical personnel during future epidemics and pandemics. Furthermore, our results indicate that relevant interventions can significantly improve sleep quality, while a prolonged break after interventions does not affect sleep quality.


Subject(s)
COVID-19/epidemiology , Medical Staff, Hospital/psychology , Pandemics/prevention & control , SARS-CoV-2 , Sleep Initiation and Maintenance Disorders/epidemiology , Sleep , Adult , Anxiety/epidemiology , COVID-19/virology , China/epidemiology , Female , Hospitals, University , Humans , Male , Surveys and Questionnaires , Young Adult
2.
World J Gastroenterol ; 25(25): 3218-3230, 2019 Jul 07.
Article in English | MEDLINE | ID: mdl-31333313

ABSTRACT

BACKGROUND: Several studies have demonstrated a correlation between esophageal cancer (EC) and perturbed urinary metabolomic profiles, but none has described the correlation between urine metabolite profiles and those of the tumor and adjacent esophageal mucosa in the same patient. AIM: To investigate how urinary metabolic phenotypes were linked to the changes in the biochemical landscape of esophageal tumors. METHODS: Nuclear magnetic resonance-based metabolomics were applied to esophageal tumor tissues and adjacent normal mucosal tissues alongside patient-matched urine samples. RESULTS: Analysis revealed that specific metabolite changes overlapped across both metrics, including glucose, glutamate, citrate, glycine, creatinine and taurine, indicating that the networks for metabolic pathway perturbations in EC, potentially involved in but not limited to disruption of fatty acid metabolism, glucose and glycolytic metabolism, tricarboxylic acid cycle and glutaminolysis. Additionally, changes in most urinary biomarkers correlated with changes in biomarker candidates in EC tissues, implying enhanced energy production for rapid cell proliferation. CONCLUSION: Overall, these associations provide evidence for distinct metabolic signatures and pathway disturbances between the tumor tissues and urine of EC patients, and changes in urinary metabolic signature could reflect reprogramming of the aforementioned metabolic pathways in EC tissues. Further investigation is needed to validate these initial findings using larger samples and to establish the underlying mechanism of EC progression.


Subject(s)
Esophageal Mucosa/metabolism , Esophageal Neoplasms/metabolism , Metabolic Networks and Pathways , Metabolomics/methods , Adult , Aged , Biomarkers, Tumor/metabolism , Biomarkers, Tumor/urine , Disease Progression , Esophageal Mucosa/pathology , Esophageal Mucosa/surgery , Esophageal Neoplasms/pathology , Esophageal Neoplasms/urine , Esophagectomy , Female , Humans , Magnetic Resonance Spectroscopy , Male , Metabolome , Middle Aged , Preoperative Period , Tumor Microenvironment , Urinalysis/methods
3.
Dig Dis Sci ; 57(12): 3178-83, 2012 Dec.
Article in English | MEDLINE | ID: mdl-22752666

ABSTRACT

BACKGROUND: Hypertrophy of non-clamped liver lobes and the atrophy of clamped lobes have been shown to be interactive. Here, a rat model of selective lobe occlusion was established to study the effect of contralateral ischemia/reperfusion (I/R) on regeneration of non-clamped lobes. METHODS: Left lateral and middle liver lobes were pretreated with I/R. In the experimental (IR + PVL) group, portal veins of the left and middle lobes were ligated. A group given similar portal vein ligation but no I/R (PVL) was the positive control. RESULTS: Compared with the PVL group, the IR + PVL had higher, but not remarkable, levels of serum transaminases; weights of non-clamped lobes in the IR + PVL group comparatively increased much more notably. At 24-h post-surgery, the IR + PVL group's PCNA mRNA was up-regulated compared with the PVL group. At 72-h post-surgery, PCNA protein was up-regulated significantly, while TGF-ß1 was down-regulated in the IR + PVL group notably, compared with the PVL group. CONCLUSION: The I/R pretreatment given to the clamped lobes facilitates liver regeneration of non-clamped lobes after selective portal vein ligation, which may result from down-regulated TGF-ß1 expression in non-clamped lobes.


Subject(s)
Liver Regeneration/physiology , Portal Vein/surgery , Reperfusion Injury/pathology , Animals , Gene Expression Regulation/physiology , Hypertrophy , Ligation , Male , Proliferating Cell Nuclear Antigen/genetics , Proliferating Cell Nuclear Antigen/metabolism , RNA/genetics , RNA/metabolism , Rats , Rats, Wistar , Real-Time Polymerase Chain Reaction , Transforming Growth Factor beta1/genetics , Transforming Growth Factor beta1/metabolism
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