Objective To analyze and compare the chemical components of the volatile oil in different parts of Cryptotae-nia japonica .Methods Essential oils were extracted from the root ,stem ,leaf ,fruit of Cryptotaenia japonica through steam distillation .GC-MS analysis combined with Kovats retention index methods were used to analyze its main components .Results 28 peaks were separated and 28 compounds were identified from volatile oils from the root of Cryptotaenia japonica ,ac-counting for 86.66% of the total ,27 peaks were separated and 27 compounds were identified from volatile oils from stem of Cryptotaenia japonica ,accounting for 88 .01% of the total ,27 peaks were separated and 27 compounds were identified from volatile oils from leaves of Cryptotaenia japonica ,accounting for 94 .03% of the total ,26 peaks were separated and 26 com-pounds were identified from volatile oils from fruit of Cryptotaenia japonica ,accounting for 88 .32% of the total .35 kinds of volatile compounds were identified from the whole strain ,and the main components of each part of the volatile oil were sesquit-erpene compounds ,containing a small amount of monoterpenes .Among all the 35 compounds ,different parts of Cryptotaenia japonica share 22 compounds .Compounds 19 ,23 only exists in the volatile oil from the roots .Aromadendrene ,compound 25 , red myrrh alcohol only exists in the volatile oil from the fruit .So there is a certain difference in the types and quantity of the compounds .Conclusion The volatile oil of Cryptotaenia japonica contains many physiologically active substance .Take the whole plant as a medicine has its rationality ,which provide a scientific basis for the further research and development of Cryp-totaenia j aponica .

Objective:To investigate correlations between blood lipid levels and clinical characteristics of patients with psoriasis vulgaris (PsV) in Fujian province.Methods:Totally, 245 PsV patients were enrolled from Department of Dermatology of the First Affiliated Hospital of Fujian Medical University from March 2019 to March 2022, and 250 gender-, age-, and body mass index-matched health checkup examinees served as controls. Their biochemical indicators, such as blood lipids, liver function, and kidney function, were evaluated. Clinical data, such as disease courses, involvement of specific sites, history of smoking and alcohol consumption, and family history of psoriasis, were collected from the PsV patients, and correlations between these clinical data and dyslipidemia were analyzed. Measurement data were compared using t test or Mann-Whitney U test, and enumeration data were compared using chi-square test. Results:There were 122 (50.8%) patients with dyslipidemia in the PsV group and 94 (37.6%) in the control group, and the prevalence of dyslipidemia significantly differed between the two groups ( χ2 = 7.48, P = 0.006). The prevalence of hypo-high-density lipoprotein cholesterolemia was significantly higher in the PsV group (29.8%) than in the control group (18.8%; χ2 = 8.15, P = 0.004). The PsV group showed significantly decreased serum levels of total cholesterol (4.5[3.9, 5.2] mmol/L), high-density-lipoprotein cholesterol (1.1[1.0, 1.3] mmol/L), and apolipoprotein A1 (1.2[1.1, 1.4] g/L) compared with the control group (4.9[4.3, 5.4] mmol/L, 1.3[1.1, 1.5] mmol/L, 1.3[1.2, 1.5] g/L, respectively; all P < 0.001). The proportions of males, patients with a history of alcohol consumption, and patients with involvement of the palmoplantar sites were significantly higher in the PsV patients with dyslipidemia (92.6%, 13.1%, 13.8%, respectively) than in those without dyslipidemia (70.7%, 6.0%, 5.0%, respectively; all P < 0.001). Multifactorial logistic regression analysis showed that "male" and "BMI ≥ 25 kg/m 2" were independent risk factors for dyslipidemia in the PsV patients ( OR [95% CI]: 3.94 [1.74, 9.74], 3.18 [1.71, 6.09], respectively), and "involvement of the palmoplantar sites" was independently associated with increased risk of hyperlipidemia ( OR [95% CI]: 3.38 [1.18, 11.01]) . Conclusion:The prevalence of dyslipidemia was higher in PsV patients than in healthy populations, and PsV patients being males, having BMI ≥ 25 kg/m 2 and with involvement of palmoplantar sites may be prone to develop lipid metabolism disorders.

Recent advancement in natural language processing (NLP) and medical imaging empowers the wide applicability of deep learning models. These developments have increased not only data understanding, but also knowledge of state-of-the-art architectures and their real-world potentials. Medical imaging researchers have recognized the limitations of only targeting images, as well as the importance of integrating multimodal inputs into medical image analysis. The lack of comprehensive surveys of the current literature, however, impedes the progress of this domain. Existing research perspectives, as well as the architectures, tasks, datasets, and performance measures examined in the present literature, are reviewed in this work, and we also provide a brief description of possible future directions in the field, aiming to provide researchers and healthcare professionals with a detailed summary of existing academic research and to provide rational insights to facilitate future research.
Humans ; Natural Language Processing ; Surveys and Questionnaires