Objective To explore the influencing factors of olfactory dysfunction in patients with Parkinson's disease(PD)and conduct a systematic review and Meta-analysis.Methods Articles on factors influencing olfactory dysfunction in PD were retrieved from databases including SinoMed,VIP,China National Knowledge Infrastructure,Wanfang Data Knowledge Service Platform,Web of Science,PubMed,Cochrane,Embase,and MEDLINE.The search period spanned from the inception of each database to November 30,2024.Results A total of 13 articles(with a total sample size of 2465)were included,with a total of 18 influencing factors summarized as two themes:core features and progression factors of PD,and individual background and environmental interaction factors.Meta-analysis showed that age(MD=1.01,95％CI:-0.46-2.49,P=0.18),smoking(OR=0.88,95％CI:0.57-1.37,P=0.57),and constipation(OR=1.22,95％CI:0.38-3.93,P=0.74)were not factors affecting olfactory dysfunction in PD patients.Conclusion Factors influencing olfactory dysfunction in PD are predominantly associated with non-motor symptoms.Intervention strategies targeting non-motor symptoms(such as improving sleep quality,vitamin D supplementation,and early cognitive training)may provide novel approaches for delaying the progression of olfactory dysfunction.

Blastocystis is a zoonotic intestinal parasite that can infect a variety of animals,including humans,and can cause symptoms such as diarrhea,abdominal pain,and bloating in both humans and animals.Although blastocystosis is widespread in the world,it has not attracted enough atten-tion,and has been listed as one of the neglected diseases by the World Health Organization.Some subtypes of Blastocystis in cattle belong to zoonotic subtypes,which have the potential risk of cross-species transmission to humans and pose a potential threat to human public health security.Therefore,understanding the prevalence,subtype distribution and diagnostic methods of Blasto-cystis in cattle is of great significance for the prevention and control of blastocystosis.Based on this,this article reviewed the subtype classification,diagnostic methods,epidemic situation and public health significance of Blastocystis in cattle,which provided an important reference for the prevention and control of blastocystosis.

Blastocystis is a zoonotic intestinal parasite that can infect a variety of animals,including humans,and can cause symptoms such as diarrhea,abdominal pain,and bloating in both humans and animals.Although blastocystosis is widespread in the world,it has not attracted enough atten-tion,and has been listed as one of the neglected diseases by the World Health Organization.Some subtypes of Blastocystis in cattle belong to zoonotic subtypes,which have the potential risk of cross-species transmission to humans and pose a potential threat to human public health security.Therefore,understanding the prevalence,subtype distribution and diagnostic methods of Blasto-cystis in cattle is of great significance for the prevention and control of blastocystosis.Based on this,this article reviewed the subtype classification,diagnostic methods,epidemic situation and public health significance of Blastocystis in cattle,which provided an important reference for the prevention and control of blastocystosis.

Objective To explore the influencing factors of olfactory dysfunction in patients with Parkinson's disease(PD)and conduct a systematic review and Meta-analysis.Methods Articles on factors influencing olfactory dysfunction in PD were retrieved from databases including SinoMed,VIP,China National Knowledge Infrastructure,Wanfang Data Knowledge Service Platform,Web of Science,PubMed,Cochrane,Embase,and MEDLINE.The search period spanned from the inception of each database to November 30,2024.Results A total of 13 articles(with a total sample size of 2465)were included,with a total of 18 influencing factors summarized as two themes:core features and progression factors of PD,and individual background and environmental interaction factors.Meta-analysis showed that age(MD=1.01,95％CI:-0.46-2.49,P=0.18),smoking(OR=0.88,95％CI:0.57-1.37,P=0.57),and constipation(OR=1.22,95％CI:0.38-3.93,P=0.74)were not factors affecting olfactory dysfunction in PD patients.Conclusion Factors influencing olfactory dysfunction in PD are predominantly associated with non-motor symptoms.Intervention strategies targeting non-motor symptoms(such as improving sleep quality,vitamin D supplementation,and early cognitive training)may provide novel approaches for delaying the progression of olfactory dysfunction.

Objective: To examine the association between sleep and frailty using the bidirectional two-sample Mendelian randomization (MR) approach, so as to provide the basis for the prevention and intervention of frailty. Methods: The data on single nucleotide polymorphisms (SNP) related to sleep duration, insomnia and morning chronotype were collected from genome-wide association studies (GWAS) and meta-analysis of GWAS, involving 446 118, 1 331 010 and 697 828 participants, respectively. The frailty was evaluated using the frailty index, and the relevant SNP data were collected from a meta-analysis of GWAS involving 175 226 participants. A bidirectional MR analysis was performed using the inverse-variance weighted method. Sensitivity analyses employed the weighted median method, the maximum likelihood-based method, the MR-Egger regression, and the MR-PRESSO test. Results: Forward MR analysis showed that longer sleep duration (β=-0.170, 95%CI: -0.255 to -0.085) and morning chronotype (β=-0.036, 95%CI: -0.058 to -0.014) decreased the risk of frailty, while insomnia increased the risk of frailty (β=0.167, 95%CI: 0.149-0.184). Reverse MR analysis showed that frailty increased the risk of insomnia (OR=1.645, 95%CI: 1.278-2.117). Both bidirectional MR results were robust, which excluded the impact of heterogeneity and horizontal pleiotropy. Conclusion Sleep duration, insomnia, and morning chronotype are associated with frailty.

Objective: To systematically evaluate the influencing factors for medication compliance in patients with comorbidities of chronic diseases, so as to provide the evidence for improving medication compliance. Methods: Literature on influencing factors for medication compliance in patients with comorbidities of chronic diseases were retrived from CNKI, Wanfang Data, VIP, SinoMed, PubMed, Web of Science, Cochrane Library and Embase from inception to January 20, 2024. After independent literature screening, data extraction, and quality assessment by two researchers, a meta-analysis was performed using RevMan 5.4 and Stata 16.0 softwares. Literature were excluded one by one for sensitivity analysis. Publication bias was assessed using Egger's test. Results: Initially, 7 365 relevant articles were retrieved, and 35 of them were finally included, with a total sample size of about 150 000 individuals. There were 30 cross-sectional studies and 5 cohort studies; and 11 high-quality studies and 24 medium-quality studies. The meta-analysis showed that the demographic factors of lower level of education (OR=2.148, 95%CI: 1.711-2.696), lower economic income (OR=1.897, 95%CI: 1.589-2.264), male (OR=0.877, 95%CI: 0.782-0.985), living alone (OR=2.833, 95%CI: 1.756-4.569) and unmarried (OR=2.784, 95%CI: 1.251-6.196); the medication treatment factors of polypharmacy (OR=1.794, 95%CI: 1.190-2.706), potentially inappropriate medication (OR=2.988, 95%CI: 1.527-5.847), low frequency of daily medication (OR=0.533, 95%CI: 0.376-0.754) and adverse drug reactions (OR=3.319, 95%CI: 1.967-5.602); the disease factors of long course of disease (OR=2.118, 95%CI: 1.643-2.730), more comorbidities (OR=1.667, 95%CI: 1.143-2.431) and cognitive impairment (OR=2.007, 95%CI: 1.401-2.874); and the psychosocial factors of poor belief in taking medication (OR=1.251, 95%CI: 1.011-1.547), poor self-rated health (OR=1.990, 95%CI: 1.571-2.522) and being guided by healthcare professionals (OR=0.151, 95%CI: 0.062-0.368) were the influencing factors for medication compliance in patients with chronic comorbidities. Conclusion The medication compliance in patients with comorbidities of chronic diseases is associated with demographic factors, pharmacological factors, disease factors and psychosocial factors, mainly including living alone, adverse drug reactions, course of disease, number of comorbidities and medication beliefs.

Objective: To conduct a scoping review on prognostic prediction models for patients with comorbidity of chronic diseases, and understand modeling methods, predictive factors and predictive effect of the models, so as to provide the reference for prognostic evaluation on patients with comorbidity of chronic diseases. Methods: Literature on prognostic prediction models for patients with comorbidity of chronic diseases was collected through SinoMed, CNKI, Wanfang Data, VIP, PubMed, Embase, Cochrane Library and Web of Science published from the time of their establishment to November 1, 2023. The quality of literature was assessed using prediction model risk of bias assessment tool (PROBAST), then modeling methods, predictive factors and predictive effects were reviewed. Results: Totally 2 130 publications were retrieved, and nine publications were finally enrolled, with an overall high risk of bias. Thirteen models were involved, with three established using machine learning methods and ten established using logistic regression. The prediction results of four models were death, with main predictive factors being age, gender, body mass index (BMI), Barthel index and pressure ulcers; the prediction results of nine models were rehospitalization, with main predictive factors being age, BMI, hospitalization frequency, duration of hospital stay and hospitalization costs. Eleven models reported the area under the receiver operating characteristic curve (AUC), ranging from 0.663 to 0.991 6; two models reported the C-index, ranging from 0.64 to 0.70. Eight models performed internal validation, one model performed external validation, and four models did not reported verification methods. Conclusions The prognostic prediction models for patients with comorbidity of chronic diseases are established by logistic regression and machine learning methods with common nursing evaluation indicators, and perform well. Laboratory indicators should be considered to add in the models to further improve the predictive effects.

Objective:To investigate the differences and applicability of free silica detection methods of different crystal forms in dust, and to provide a basis for the selection of various methods.Methods:From December 2021 to June 2022, dust samples from 20 enterprises in different industries in 18 cities in Henan Province were randomly selected as the investigation objects. X-ray diffraction (XRD) method was used to analyze the samples and classify the samples. Based on GBZ/T 192.4-2007 "Determination of Dust in the Air of Workplace-Part 4: Content of Free Silica in Dust", pyrophosphate method and infrared spectrophotometry were used for quantitative determination. The measured results were analyzed by paired sample t test to evaluate the advantages and disadvantages of the two methods and their applicable scope. Results:The XRD results of 20 dust samples could be divided into α, β, γ crystal types and the mixed type of α and γ. There was no significant difference between pyrophosphate method and infrared spectrophotometry ( P=0.180). The pyrophosphate method results of β, γ and α, γ mixed crystalline free silica were significantly higher than those of infrared spectrophotometry, and the difference was statistically significant ( P<0.001) . Conclusion:Pyrophosphate method and infrared spectrophotometry are suitable for α-type free silica, while pyrophosphate method is suitable for β, γ and α, γ mixed crystalline free silica.

Objective:To investigate the differences and applicability of free silica detection methods of different crystal forms in dust, and to provide a basis for the selection of various methods.Methods:From December 2021 to June 2022, dust samples from 20 enterprises in different industries in 18 cities in Henan Province were randomly selected as the investigation objects. X-ray diffraction (XRD) method was used to analyze the samples and classify the samples. Based on GBZ/T 192.4-2007 "Determination of Dust in the Air of Workplace-Part 4: Content of Free Silica in Dust", pyrophosphate method and infrared spectrophotometry were used for quantitative determination. The measured results were analyzed by paired sample t test to evaluate the advantages and disadvantages of the two methods and their applicable scope. Results:The XRD results of 20 dust samples could be divided into α, β, γ crystal types and the mixed type of α and γ. There was no significant difference between pyrophosphate method and infrared spectrophotometry ( P=0.180). The pyrophosphate method results of β, γ and α, γ mixed crystalline free silica were significantly higher than those of infrared spectrophotometry, and the difference was statistically significant ( P<0.001) . Conclusion:Pyrophosphate method and infrared spectrophotometry are suitable for α-type free silica, while pyrophosphate method is suitable for β, γ and α, γ mixed crystalline free silica.

Objective To assess the causality between 14 malignant tumors and hypertension.Methods Publicly available datasets from genome-wide association study were used,from which independent genetic variants strongly associated with hypertension and 14 malignant tumors were extracted as instrumental variables for bidirectional Mendelian randomization(MR)analysis,including random effect inverse variance weighted(IVW),simple mode,weighted median,weighted mode and MR-Egger to evaluate the causal effect.Sensitivity analysis was used to test the validity and robustness of the analytical results,and multivariate MR method was used to further control for the effects of confounding factors.Results In the MR analysis of malignant melanoma and hypertension,the study included a total of 11 single nucleotide polymorphisms(SNPs)strongly associated with malignant melanoma.After Bonferroni correction,the IVW-based results showed a causal relationship between malignant melanoma and hypertension(OR=1.67,95％CI:1.27-2.21,P＜0.001).Cochran's Q test,Mendelian randomization pleiotropy residual sum and outlier test and MR-Egger intercept test showed that there were no outliers and no horizontal pleiotropy among the instrumental variables,and the sensitivity analysis of the leave-one-out method showed that there was no single SNP that had a significant impact on the overall results.In the analysis of hypertension and leukemia,the preliminary analysis results showed that there may be a relationship between the two,but after adjusting for confounders,the effect of hypertension on the risk of leukemia was no longer significant.Conclusion Malignant melanoma may be a risk factor in the development of hypertension.