Objective To analyze the differences in microbial communities in bronchoalveolar lavage fluid (BALF) from patients with simple pneumonia versus those with chronic obstructive pulmonary disease (COPD) combined with lower respiratory tract infection using metagenomic next-generation sequencing (mNGS). Methods Patients hospitalized for pulmonary infections at the First Affiliated Hospital of Xinjiang Medical University between December 2021 and March 2023 were included. Based on the presence of COPD, the patients were divided into two groups: those with simple pneumonia and those with COPD combined with lower respiratory tract infection. mNGS was employed to detect microbes in BALF, and the microbial community distribution characteristics of the two groups were analyzed. Results A total of 97 patients were included, of whom 80 (81.82%) had positive microbial detection results. The smoking index in COPD group with lower respiratory tract infection was significantly higher than that in the group with simple pneumonia (t= −3.62, P=0.001). Differences in microbial community distributions were observed between the groups. At the genus level, 19 species of microorganisms were detected in the simple pneumoniapulmonary infection group, including 8 bacteria (42.11%), 2 fungi (10.53%), 3 viruses (15.79%), and 6 other types of microorganisms (31.58%). In contrast, 22 types of microbes were detected in COPD group with lower respiratory tract infection, including 10 bacteria (47.62%), 3 fungi (14.29%), 4 viruses (19.05%), and 4 other types of microorganisms (19.05%). Differences were also noted in reads per million (RPM) values; bacterial RPM values at the genus level were significantly higher in the COPD group during non-severe pneumonia compared to the simple pneumonia group (Z=–2.706, P=0.007). In the patients with severe pneumonia, RPM values at the genus and species levels were significantly higher than those in non-severe pneumonia (Z=−2.202, P=0.028; Z=−2.141, P=0.032). In COPD combined with severe pneumonia, bacterial RPM values were significantly higher at the species level compared to non-severe pneumonia (Z=−2.367, P=0.017). ConclusionsThere are differences in the distribution of microbial communities at the genus and species levels in BALF from patients with COPD combined with lower respiratory tract infection compared to those with simple pulmonary pneumonia. Bacteria are the predominant microbial type in both groups, but the dominant bacterial species differ between them. Simple pneumonia are primarily associated with bacterial, viral, and other types of microbial infections, while COPD combined with lower respiratory tract infection is predominantly associated with fungal and bacterial infections. RPM values may serve as an indicator of the severity of pneumonia.
Acute zonal occult outer retinopathy (AZOOR) is an acquired retinal diseases. The majority of patients who develop AZOOR are women characterized by an acute onset of visual blurred and scotoma with photopsias. The fundus examination is often normal or appeared mild abnormal. The RPE atrophy of fundus is similar with white syndrome. Although FFA and ICGA features are either unremarkable or unrelated to AZOOR, there are still important in differential diagnosis. The characteristic abnormalities appearance of FAF (complicated and varied), OCT (regional anomaly of ellipsoid zone), visual field (visual field defect) and ERG (decreased amplitude and prolonged latency of rod reaction, maximum reaction, cone reaction and scintillation reaction) are considered critical examinations to the diagnosis of AZOOR. Although there is no effective therapy for AZOOR, it has some self-limitation.
The temperature during the brain tumor therapy using high-intensity focused ultrasound (HIFU) should be controlled strictly. This research aimed at realizing uniform temperature distribution in the focal region by adjusting driving signals of phased array transducer. The three-dimensional simulation model imitating craniotomy HIFU brain tumor treatment was established based on an 82-element transducer and the computed tomography (CT) data of a volunteer's head was used to calculate and modulate the temperature distributions using the finite difference in time domain (FDTD) method. Two signals which focus at two preset targets with a certain distance were superimposed to emit each transducer element. Then the temperature distribution was modulated by changing the triggering time delay and amplitudes of the two signals. The results showed that when the distance between the two targets was within a certain range, a focal region with uniform temperature distribution could be created. And also the volume of focal region formed by one irradiation could be adjusted. The simulation results would provide theoretical method and reference for HIFU applying in clinical brain tumor treatment safely and effectively.
Missing data represent a general problem in many scientific fields, especially in medical survival analysis. Dealing with censored data, interpolation method is one of important methods. However, most of the interpolation methods replace the censored data with the exact data, which will distort the real distribution of the censored data and reduce the probability of the real data falling into the interpolation data. In order to solve this problem, we in this paper propose a nonparametric method of estimating the survival function of right-censored and interval-censored data and compare its performance to SC (self-consistent) algorithm. Comparing to the average interpolation and the nearest neighbor interpolation method, the proposed method in this paper replaces the right-censored data with the interval-censored data, and greatly improves the probability of the real data falling into imputation interval. Then it bases on the empirical distribution theory to estimate the survival function of right-censored and interval-censored data. The results of numerical examples and a real breast cancer data set demonstrated that the proposed method had higher accuracy and better robustness for the different proportion of the censored data. This paper provides a good method to compare the clinical treatments performance with estimation of the survival data of the patients. This provides some help to the medical survival data analysis.
Objective To evaluate the result of treating nonunion of lower segment of humerus with combination of rib flaps of cross chest and double plates. Methods From Feburary 2000 to May 2006, 21 cases of nounion of lower segment of humerus were treated. There were 13 males and 8 females with an average age of 36.5 years (range, 17-56 years). Accordingto AO classification, there were 5 cases of type A1.3, 7 cases of type B1.3, 6 cases of type B2.3, 2 cases of type B3.3, and 1 case of type C1.3. All nonunion occurred after internal fixation, which was caused by bone resorption at fracture end in 12 cases, by plates breakage in 3 cases, and by internal fixation loosening in 6 cases; including 8 cases of hypertrophic nonunion and 13 cases of atrophy nonunion without pseudoarthrosis. An average time of nonunion was 1.5 years (from 8 months to 3 years). All cases were treated with combination of rib flaps of cross chest (length, 3.0-3.5 cm) and double plates. The pedicle was divided 8 to 10 weeks after operation and all cases carried out functional exercise. Results The patients were followed up for an average time of 18.2 months (range, 1-3 years). All nounion of lower segment of humerus were healed and no radial nerve injury occurred. Primary heal ing of wound was achieved at both donor and recipient sites. Bony union was achieved in all cases after an average time of 3.5 months (range, 3-5 months) after operation. According to the the Hospital for Special Surgery (HSS) functional elbow index, the average score was 89.3 (range, 81.7-92.5) and the outcome was excellent in 14 cases, good in 4 cases, and poor in 3 cases, the excellent and good rate was 85.7%. Conclusion Combination of rib flaps of cross chest and double plates is an effective method of treating nonunion of lower segment of humerus.
The research on brain functional mechanism and cognitive status based on brain network has the vital significance. According to a time–frequency method, partial directed coherence (PDC), for measuring directional interactions over time and frequency from scalp-recorded electroencephalogram (EEG) signals, this paper proposed dynamic PDC (dPDC) method to model the brain network for motor imagery. The parameters attributes (out-degree, in-degree, clustering coefficient and eccentricity) of effective network for 9 subjects were calculated based on dataset from BCI competitions IV in 2008, and then the interaction between different locations for the network character and significance of motor imagery was analyzed. The clustering coefficients for both groups were higher than those of the random network and the path length was close to that of random network. These experimental results show that the effective network has a small world property. The analysis of the network parameter attributes for the left and right hands verified that there was a significant difference on ROI2 (P = 0.007) and ROI3 (P = 0.002) regions for out-degree. The information flows of effective network based dPDC algorithm among different brain regions illustrated the active regions for motor imagery mainly located in fronto-central regions (ROI2 and ROI3) and parieto-occipital regions (ROI5 and ROI6). Therefore, the effective network based dPDC algorithm can be effective to reflect the change of imagery motor, and can be used as a practical index to research neural mechanisms.
ObjectiveTo analyze the distribution, prognostic differences, and characteristics of patients with colorectal cancer (CRC) from 2007 to 2022 based on the current version of the Database from Colorectal Cancer (DACCA), so as to provide a basis for clinical decision-making. MethodsThe eligible CRC patients based on the established screening criteria from the updated DACCA were collected. The distribution and survival status of CRC patients in different residence places were analyzed. The residence places included 21 cities (prefectures) within Sichuan Province. ResultsA total of 5 416 cases that met the screening criteria from 2007 to 2022 were collected. Among these, CRC patients were predominantly concentrated in Chengdu (44.77%), Meishan (5.78%), and Nanchong (4.56%) cities. A heatmap depicting the superimposed trend of CRC patients origins revealed the distribution of patients was basically divided into eastern and western regions along the axis of “Mianyang–Chengdu–Yaan cities”. The majority of patients (5 359 cases, 98.95%) was distributed in the eastern region, while a few in the western region (57 cases, 1.05%). The patients in the eastern region were more high clustered (especially Chengdu city), while those in the western region was sporadically dispersed, and the patients in the western region increased slowly without aggregation. The 1, 3, and 5-year cumulative overall survival rates of the CRC patients in the DACCA were 96.2%, 89.7%, and 85.1%, respectively. The multivariate Cox proportional hazards regression model showed that the male, age ≥35-year old, adenocarcinoma (mucinous adenocarcinoma as a reference), poorly differentiated degree, pTNM stages Ⅲ and Ⅳ, obstruction, and perforation were the risk factors for median overall survival shortening in the CRC patients (all P<0.05). The survival curve of patients with CRC drawn by Kaplan-Meier method showed that the overall survival of CRC patients in different cities (prefectures) had no statistical differences as compared with the integral CRC patients (P>0.05), except for Neijiang city (was worse than that of the integral CRC patients, P<0.05). ConclusionsBased on data analysis for the DACCA from 2007 to 2022, the majority of CRC patients clusters in the eastern region. Chengdu city exhibits a high clustering, while the western region shows a sporadic distribution without aggregation phenomena. It is found that the cumulative overall survival of CRC patients in Neijiang city is worse than that of the integral CRC patients, while which in the other cities (prefectures) was relatively close to that of the integral CRC patients in Sichuan Province.
ObjectiveStudy how to quantify the bias of each study and how to estimate them. MethodIn the random-effect model, it is commonly assumed that the effect size of each study in meta-analysis follows a skew normal distribution which has different shape parameter. Through introducing a shape parameter to quantify the bias and making use of Markov estimation as well as maximum likelihood estimation to estimate the overall effect size, bias of each study, heterogeneity variance. ResultIn simulation study, the result was closer to the real value when the effect size followed a skew normal distribution with different shape parameter and the impact of heterogeneity of random effects meta-analysis model based on the skew normal distribution with different shape parameter was smaller than it in a random effects metaanalysis model. Moreover, in this specific example, the length of the 95%CI of the overall effect size was shorter compared with the model based on the normal distribution. ConclusionIncorporate the bias of each study into the random effects meta-analysis model and by quantifying the bias of each study we can eliminate the influence of heterogeneity caused by bias on the pooled estimate, which further make the pooled estimate closer to its true value.
ObjectiveTo analyze the clinical characteristics and geographical distribution of Keshan disease in Chongqing city for prevention and disease control. MethodsWe collected the clinical data of patients with Keshan disease from 2008 to 2012 in Liangping, Shizhu, Fengdu and Dianjiang counties as well as Wanzhou district of Chongqing city including the medical history, physical examination, results of laboratory tests to analyze the clinical characteristics and geographical distribution. ResultsFifty-eight patients were included from Liangping (n=21), Shizhu (n=25), Fengdu (n=11) and Dianjiang (n=1). The number of patients with potential and chronic Keshan disease was 16 and 42, respectively. The average age of patients was 54.91±15.53 years. The proportion above age 60 was 32.76% and below age 10 was 3.45%. The patients had main clinical signs as heart enlargement (36.76%), low-weak first heart sound (22.41%), systolic murmur (10.34%), arrhythmia (8.62%), etc. Abnormal ECG detection rate was 98.28%, with common types followed by sinus rhythm (37.93%), complete right bundle branch block (25.86%), ST-T changes (24.14%), left ventricular hypertrophy (15.52%), atrial fibrillation (13.79%), occasional ventricular premature (10.34%), T changes (10.34%), sinus bradycardia (8.62%), and incomplete right bundle branch block (6.90%). X-ray results showed that heart enlargement accounted for 82.76%. The ratios of mild, moderate and significant expansion of the heart were 46.55%, 27.59%, and 8.62%, respectively. ConclusionIn recent years, most patients with Keshan disease in Chongqing are chronic type at older age. The main clinical symptom is heart enlargement with high abnormal ECG detection rate.
ObjectiveThe purpose of the research is to study the distribution and early warning of electroencephalogram (EEG) in acute mountain sickness (AMS). MethodsA total of 280 healthy young men were recruited from September 2016 to October 2016. The basic data were collected by the centralized flow method, the general situation of the division of the investigators after the training, the Lewis Lake score, the computer self-rating anxiety scale and depression scale, and the collection of EEG. Follow up in three months. Results94 of the patients with AMS, morbidity is 33%, 21 (22.34%) of the patients are moderate to severe, 73 (77.66%) are mild, morbidity is 26.67%. The abnormal detection rate of electrogram was 7.9% (22/280), which were mild EEG, normal EEG abnormal rate was 8.6% (16/186), abnormal detection rate of mild AMS was 4.1% (3/73), and the abnormal detection rate was 14.3% (3/21) in the medium / heavy AMS. The latter was significantly different from the previous (P < 0.05). Three months follow-up of this group of patients with 0 case of high altitude disease. Conclusions The EEG in AMS is mainly a rhythm irregular, unstable, poor amplitude modulation; or two hemisphere volatility difference of more than 50% or slightly increased activity. The result is statistically significant, suggesting that EEG distributions has possible early warning of AMS.