Search

In the current study, an electronic nose (E-nose) and gas chromatography–ion mobility spectrometry (GC-IMS) were employed to investigate the volatile flavor compounds (VFCs) of intense flavor beef tallow (L) and ordinary beef tallow (P). The study results indicate that an E-nose combined with an LDA and GC-IMS combined with an OPLS-DA can effectively distinguish between the two types of beef tallow. Compared with ordinary beef tallow, the E-nose sensors of intense flavor beef tallow have stronger response signals to sulfides, terpenes, and nitrogen oxides. A total of 22 compounds contribute to making the flavor of intense flavor beef tallow more typical and richer; in contrast, ethyl acetate was the main aroma-active compound found in the ordinary beef tallow. Sulfur-containing compounds and terpenoids might be the key substances that cause sensory flavor differences between the two types of beef tallow. In conclusion, the results of this study clarify the characteristics and differences of the two types of beef tallow and provide an enhanced understanding of the differences in the flavors of the two types of beef tallow. [ABSTRACT FROM AUTHOR]

Hip fracture is a severe complication in the elderly. The affected people are at a higher risk of second fracture and death occurrence, and the best treatment for hip fractures is still being debated. Aside from the treatment, many factors, such as comorbidity conditions, may be associated with second fracture and death occurrence. This study aims to identify effective treatments and important covariates and estimate their effects on the progression of second fracture and death occurrence in hip fracture elderly patients using the semi-competing risks framework, because death dependently censors a second fracture but not vice versa. Due to the complex semi-competing risks data, performing variable selection simultaneously for second fracture and death occurrence is difficult. We propose a penalised semi-parametric copula method for semi-competing risks data. Specifically, we use separate Cox semi-parametric models for both margins and employ a copula to model the two margins' dependence. We develop a coordinate-wise optimisation algorithm that takes into account the data structure and copula function's complexities. Simulations show that the proposed method outperforms the traditional penalised marginal method. We apply the proposed method to a population-based cohort study of hip fracture elderly patients, providing new insights into their treatment and clinical management. [ABSTRACT FROM AUTHOR]

Patients with chronic diseases, such as cancer or epilepsy, are often followed through multiple stages of clinical interventions. Dynamic treatment regimes (DTRs) are sequences of decision rules that assign treatments at each stage based on measured covariates for each patient. A DTR is said to be optimal if the expectation of the desirable clinical benefit reaches a maximum when applied to a population. When there are three or more options for treatments at each decision point and the clinical outcome of interest is a time-to-event variable, estimating an optimal DTR can be complicated. We propose a doubly robust method to estimate optimal DTRs with multicategory treatments and survival outcomes. A novel blip function is defined to measure the difference in expected outcomes among treatments, and a doubly robust weighted least squares algorithm is designed for parameter estimation. Simulations using various weight functions and scenarios support the advantages of the proposed method in estimating optimal DTRs over existing approaches. We further illustrate the practical value of our method by applying it to data from the Standard and New Antiepileptic Drugs study. In this analysis, the proposed method supports the use of the new drug lamotrigine over the standard option carbamazepine. When the actual treatments match the estimated optimal treatments, survival outcomes tend to be better. The newly developed method provides a practical approach for clinicians that is not limited to cases of binary treatment options. [ABSTRACT FROM AUTHOR]

Objective To explore the prognostic factors that affect patients with advanced esophageal cancer treated with Traditional Chinese medicine (TCM). Methods A total of 72 patients with stage IV esophageal cancer were selected for analysis, and the advantaged and disadvantaged groups of TCM treatment were defined according to survival time. The log-rank method was used for the univariate analysis, the rank-sum test was used for the correlation between the syndrome type and the prognostic grouping, and the Cox proportional risk model was used for multiple factors. Results The median survival of the 72 patients with esophageal cancer was 17.9 months. The univariate analysis of the result showed that the presence of organ metastasis, the presence of lung metastasis, and the post-treatment symptom self-assessment and length of herbal medication were related to the prognosis of advanced esophageal cancer treated with TCM. The rank-sum test between the TCM syndrome elements, and survival prognosis grouping showed that the syndrome element of Qi stagnation may also affect prognosis. The result of the multi-factorial analysis showed that the factor of the duration of the TCM administration was an independent factor that affects the prognosis of advanced esophageal cancer treated with TCM. Conclusion The duration of TCM treatment affected the prognosis of patients with advanced esophageal cancer. [ABSTRACT FROM AUTHOR]

Objective To explore whether early treatment with integrated Chinese and western medicine can prolong the survival time of patients with advanced digestive tract malignant tumors using a new statistical analysis method and real-world data. Methods Based on the left truncated data, the Copula model was used to construct a joint model of the time from stage IV diagnosis to treatment and the time to overall survival. The estimated value and significance of the Copula dependence parameter, η, were obtained to evaluate the dependence strength between the two event times of interest. Results The numerical simulation showed that this method performed well when the left truncation rate was 20%. The estimated Copula dependence parameter η), in the real data analysis was 0.279 (P<0.05), indicating that there was a significant correlation between times to treatment and overall survival. Gender, the Eastern Cooperative Oncology Group score, targeted treatment, and metastatic site 1 were significant factors associated with overall survival. Conclusion The new statistical method provided valuable insights and analytical tools for the effectiveness of integrated traditional Chinese and western medicine in treating patients with advanced digestive tract malignant tumors. [ABSTRACT FROM AUTHOR]

To improve the gelling property of konjac gum (KGM) and enhance the application value of Abelmoschus manihot (L.) medic gum (AMG), a novel type of gel was prepared using KGM and AMG in this study. The effects of AMG content, heating temperature and salt ions on the characteristics of KGM/AMG composite gels were studied by Fourier transform infrared spectroscopy (FTIR), zeta potential, texture analysis and dynamic rheological behavior analysis. The results indicated that the AMG content, heating temperature and salt ions could affect the gel strength of KGM/AMG composite gels. Hardness, springiness, resilience, G′, G* and η* of KGM/AMG composite gels increased when AMG content increased from 0 to 2.0 %, but they decreased when AMG increased from 2.0 % to 3.5 %. High-temperature treatment significantly enhanced the texture and rheological properties of KGM/AMG composite gels. The addition of salt ions reduced the zeta potential absolute value and weakened the texture and rheological properties of KGM/AMG composite gels. Furthermore, the KGM/AMG composite gels could be classified as non-covalent gels. The non-covalent linkages included hydrogen bonding and electrostatic interactions. These findings would help understand the properties and formation mechanism of KGM/AMG composite gels and help improve the application value of KGM and AMG. [ABSTRACT FROM AUTHOR]

Background: Fatigue is a common source of distress for cancer survivors. The severity of cancer-related fatigue varies significantly, which may be due to individual differences in host factors., Aim: This cross-sectional study aims to explore how demographic, oncological, sociological, psychological, and stress-related hormones levels interact to influence the distinct experiences of fatigue (Cancer-related fatigue [CRF] occurrence and fatigue degree)., Methods: A cross-sectional study carried out at the oncology outpatient and ward department of Xiyuan Hospital of China Academy of Chinese Medical Sciences recruited 306 cancer patients between January 2021 to December 2021. General information, fatigue, psychological factors was evaluated by general information questionnaire, the Revised Piper's Fatigue Scale-Chinese Version (RPFS-CV), and the self-report Hospital Anxiety and Depression Scale (HADS). Stress-related hormones were measured with chemiluminescent enzyme immunoassay (Zhengzhou Antobio)., Results: 306 patients were included, 229 (74.8%) were diagnosed with CRF, including 94 (41.0%) with mild fatigue, 121 (52.8%) with moderate fatigue, and 14 (6.1%) with severe fatigue. Multivariate regression analysis showed that higher depression scores, aldosterone levels may increase the risk of CRF. Patients who are obese (Body mass index ≥ 28 kg/m 2 ) may help to reduce the risk of CRF. Other contributing factors for increased levels of fatigue ( p < 0.05) include being female, having anxiety, depression and high aldosterone levels., Conclusion: The research suggested that CRF was a common symptom in cancer survivors and pay attention to these influencing factors may help to better identify patients susceptible to fatigue and provide long-term, targeted interventions., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2023 Gu, Xu, Zhu, Lam, Yi, Gong, Wang, Guo, Fu, Shi, Wang and Liu.)