OBJECTIVE: Fear of progression (FoP) leads to poor clinical outcomes in colorectal cancer patients. The study aimed to clarify the profiles and influencing factors of FoP among colorectal cancer patients.
METHODS: A cross-sectional study was conducted with 409 colorectal cancer patients. Convenience sampling method was used to select colorectal cancer patients hospitalized in a tertiary-level hospital in Nanjing as the survey subjects. General information questionnaire, Fear of Progression Questionnaire-Short Form, Distress Disclosure Index, and Social Support Rating Scale were used to collect the data. Latent profile analysis was used to explore the latent profiles of FoP in colorectal cancer patients. Additionally, the influencing factors of profiles were explored by Univariate Analysis and Binomial Logistic Regression Analysis.
RESULTS: Latent profile analysis identified two subgroups of fear of disease progression: the \"fear low-risk profile (83%)\", and the \"severe fear profile (17%).\" Patients with low age, low social support utilization, first hospital admission, severe healthcare burden, and preoperative bowel symptoms were prone to severe fear of disease progression.
CONCLUSIONS: There is some heterogeneity in the level of postoperative fear of disease progression in colorectal cancer patients. Doctors and nurses should focus on patients with severe fear and take targeted preventive and psychological care for patients\' fear of disease progression as early as possible according to the distribution characteristics of different categories.

UNASSIGNED: To preliminarily assess the prevalence and control effect of tuberculosis and drug-resistant tuberculosis (TB) in Anhui province, and analyze the trends in the changing drug resistance spectrum of Mycobacterium tuberculosis (Mtb) isolated in Anhui province from 2016 to 2022.
UNASSIGNED: From 2016 to 2022, a total of 2336 culture-positive tuberculosis strains were collected from four drug resistance monitoring sites. Patient demographic information was collected and drug susceptibility testing was conducted.
UNASSIGNED: Among the 2336 Mycobacterium tuberculosis complex strains, 1788 (76.54%) were from male patients and 548 (23.46%) were from female patients. The majority were of Han ethnicity, from rural areas, and employed in agriculture, with 12.54% (285/2273) having diabetes. A total of 1893 (81.04%) strains were sensitive to all six anti-TB drugs tested, and 443 (18.96%) strains were resistant to at least one or more anti-TB drugs. The drug resistance rate for patients undergoing initial treatment was 16.80% (348/2071), and 35.85% (95/265) for those receiving retreatment. Among the six anti-TB drugs, the resistance rates from highest to lowest were: INH (10.55%, 236/2336), SM (8.18%, 183/2336), OFX (6.53%, 146/2336), RFP (5.95%, 133/2336), EMB (2.37%, 53/2336), KM (1.97%, 44/2336). Significant differences were observed in MDR strains across different ages, types, with or without diabetes, and geographical sources (χ2=14.895,76.534,6.032,5.109, all P<0.05).
UNASSIGNED: The tuberculosis prevention and control measures have controlled the drug resistance rate of Mycobacterium tuberculosis to a certain extent. However, there are still statistical differences in drug resistance rates among TB patients with different categories, age groups, regions, and diabetic diseases. Early detection and prompt treatment of patients with drug-resistant TB remain critical to controlling the spread of this disease.

OBJECTIVE: To analyze the epidemiological characteristics of leptospirosis in China from 2010 to 2022, so as to provide insights into formulation of the leptospirosis control strategy.
METHODS: All data pertaining to clinically diagnosed cases and confirmed cases of leptospirosis reported in China from January 1, 2010 to December 31, 2022 was collected from Chinese Disease Prevention and Control Information Management System. The spatial, temporal and population distributions, and report and diagnosis institutions of leptospirosis cases were analyzed using a descriptive epidemiological method.
RESULTS: A total of 4 559 leptospirosis cases were reported in China from 2010 to 2022, with an annual average number of 351 cases, and the number of reported leptospirosis cases reduced from 679 cases in 2010 to 158 cases in 2018. A total of 4 276 leptospirosis cases were reported in Sichuan Province, Yunnan Province, Guangdong Province, Hunan Province, Fujian Province, Zhejiang Province, Guangxi Zhuang Autonomous Region, Anhui Province, Jiangxi Province and Guizhou Province, accounting for 93.79% of the total number of leptospirosis cases in China. The number of leptospirosis cases had recently appeared a remarkable decline in Yunnan Province, while a significant rise was seen in the number of leptospirosis cases in two provinces of Zhejiang and Guangdong. No leptospirosis cases were reported in Henan Province from 2010 to 2020; however, there were 5 cases and 2 cases reported in 2021 and 2022, respectively. There was only one leptospirosis case reported in Shaanxi Province from 2010 to 2017; however, leptospirosis cases were reported in the province for 5 consecutive years since 2018. Leptospirosis cases were reported throughout the year in China from 2010 to 2022, with the peak of incidence found during the period between August and October, and the peak of leptospirosis incidence varied in provinces. A higher number of leptospirosis cases was seen among men than among women, with a male to female ratio of 2.3:1, and the median age of leptospirosis cases was 50 years (interquartile range, 23 years), with the highest proportion of leptospirosis cases reported at ages of 51 to 60 years (23.21%). Among all reported leptospirosis cases, 53.28% were confirmed cases, and the proportion of confirmed cases increased from 35.05% in 2010 to 61.66% in 2022. In addition, there were 67.22% of leptospirosis cases (2 937 cases) reported by comprehensive hospitals, 20.44% (893 cases) by disease control and prevention institutions, 7.23% (316 cases) by grassroots healthcare institutions and 5.10% (223 cases) by other healthcare and medical institutions, and the mortality of reported leptospirosis cases was 1.07% in China from 2010 to 2022, with a higher mortality seen among men than among women (1.39% vs. 0.36%; χ2 = 9.52, P = 0.002).
CONCLUSIONS: The incidence of leptospirosis remained at a low level in China from 2010 to 2022, and southern China was still the main endemic area for leptospirosis. The epidemiological characteristics of leptospirosis cases varied in endemic provinces, and leptospirosis cases had been continued to be reported in Shaanxi and Henan provinces, which should be paid much attention to. Intensified surveillance of leptospirosis, improved diagnosis and treatment capability of leptospirosis cases and leptospirosis control with adaptations to local circumstance are recommended.
［摘要］ 目的 分析 2010—2022 年我国钩端螺旋体病流行病学特征, 为制订钩端螺旋体病防控策略提供参考依据。方法 在中国疾病预防控制信息系统中, 收集 2010 年 1 月 1 日至 2022 年 12 月 31 日报告的钩端螺旋体病临床诊断病例和确 诊病例信息, 采用描述性流行病学方法对病例地区、时间、人群分布及报告和诊断机构进行分析。结果 2010—2022 年 全国累计报告钩端螺旋体病病例 4 559 例, 年均报告 351 例; 报告病例数从 2010 年的 679 例下降至 2018 年的 158 例。四 川省、云南省、广东省、湖南省、福建省、浙江省、广西壮族自治区、安徽省、江西省和贵州省累计报告钩端螺旋体病病例 4 276 例, 占全国病例总数的 93.79%; 其中云南省近年病例数大幅下降, 浙江省、广东省报告病例数明显增加。2010—2020 年河南省无钩端螺旋体病病例报告, 但 2021、2022 年分别报告 5 例和 2 例; 2010—2017 年陕西省仅报告 1 例病例, 但 自 2018 年起连续 5 年有病例报告。全国全年均有钩端螺旋体病病例报告, 以 8—10 月为发病高峰, 各省发病高峰存在差 异; 男性病例多于女性, 男女性别比为 2.3:1; 病例中位年龄 50 岁 (四分位间距: 23 岁), 以 51～60 岁组报告病例数占比最 高 (23.21%)。2010—2022 年我国钩端螺旋体病报告病例中, 确诊病例占 53.28%, 确诊病例占比从 2010 年的 35.05% 上升 至 2022 年的 61.66%。综合医院、疾病预防控制机构、基层卫生机构和其他卫生机构钩端螺旋体病报告病例数占比分别 为 67.22% (2 937 例)、20.44% (893 例)、7.23% (316 例)、5.10% (223 例)。2010—2022 年全国钩端螺旋体病报告病例病死 率为1.07%, 男性病死率高于女性 (1.39% vs. 0.36%; χ2 = 9.52, P = 0.002)。结论 2010—2022 年我国钩端螺旋体病处于 低水平流行状态, 南方地区为主要流行区, 各流行省份病例流行病学特征存在差异。陕西省、河南省等省份近年持续有 病例报告, 需加强关注。建议各地加强钩端螺旋体病监测, 提升病例诊治能力, 因地制宜开展防控工作。.

Features of shell and genitalia as well as nucleotide sequences of selected mitochondrial and nuclear genes of specimens of Monachacantiana from ten northern French and two Dutch populations were compared with the same features of British and Italian populations. They were found to be very similar to populations previously identified as belonging to the CAN-1 lineage of M.cantiana. This confirms previous suggestions that M.cantiana was introduced to western Europe (England, France and the Netherlands) in historical times.

BACKGROUND: Lung Large cell neuroendocrine carcinoma (LCNEC) is a rare, aggressive, high-grade neuroendocrine carcinoma with a poor prognosis, mainly seen in elderly men. To date, we have found no studies on predictive models for LCNEC.
METHODS: We extracted data from the Surveillance, Epidemiology, and End Results (SEER) database of confirmed LCNEC from 2010 to 2018. Univariate and multivariate Cox proportional risk regression analyses were used to identify independent risk factors, and then we constructed a novel nomogram and assessed the predictive effectiveness by receiver operating characteristic (ROC) curves, calibration curves, and decision curve analysis (DCA).
RESULTS: A total of 2546 patients with LCNEC were included, excluding those diagnosed with autopsy or death certificate, tumor, lymph node, metastasis (TNM) stage, tumor grade deficiency, etc., and finally, a total of 743 cases were included in the study. After univariate and multivariate analyses, we concluded that the independent risk factors were N stage, intrapulmonary metastasis, bone metastasis, brain metastasis, and surgical intervention. The results of ROC curves, calibration curves, and DCA in the training and validation groups confirmed that the nomogram could accurately predict the prognosis.
CONCLUSIONS: The nomogram obtained from our study is expected to be a useful tool for personalized prognostic prediction of LCNEC patients, which may help in clinical decision-making.

UNASSIGNED: Determine the geographic and per capita distribution of otology-neurotology physician-surgeons within the United States.
UNASSIGNED: National database review.
UNASSIGNED: United States.
UNASSIGNED: The American Neurotology Society and ENThealth.org membership databases were queried to identify otology-neurotology physician-surgeons within the United States. Physician-surgeons were divided by regional national census areas, state, and by largest population statistical area based on 2019 US Census population estimates. The number of otology-neurotology physician-surgeons per 1 million persons was calculated for each population designation.
UNASSIGNED: Four-hundred eighty-two physician-surgeons were identified, representing 49 states and the District of Columbia. The New England division (Connecticut, Maine, Massachusetts, New Hampshire, Rhode Island) was the most concentrated region (1.89), whereas the West-South-Central (Texas, Oklahoma, Arkansas, Louisiana) was the least concentrated region (1.23) per million persons. The highest concentration of physician-surgeons by state is within the District of Columbia (4.25), Vermont (3.21), North Dakota (2.62), Massachusetts (2.61), and New York (2.21) (per million), whereas Mississippi (0.67), Georgia (0.66), Idaho (0.56), New Mexico (0.48), and Wyoming (0.0) were the least concentrated per million persons. Increasing number of physician-surgeons was significantly correlated by state (r2 = 0.9; P < 0.0001), largest statistical area (r2 = 0.88; P < 0.0001), and census region (r2 = 0.95; P < 0.0005).
UNASSIGNED: Otology-neurotology physician-surgeons are evenly distributed across the United States; however, certain areas are likely underrepresented. Variability in clinical practice may account for under or overrepresentation not captured in this analysis.

In recent years, dam failures have occurred frequently because of extreme weather, posing a significant threat to downstream residents. The establishment of emergency shelters is crucial for reducing casualties. The selection of suitable shelters depends on key information such as the number and distribution of affected people, and the effective capacity and accessibility of the shelters. However, previous studies on siting shelters did not fully consider population distribution differences at a finer scale. This limitation hinders the accuracy of estimating the number of affected people. In addition, most studies ignored the impact of extreme rainfall on the effective capacity and accessibility of shelters, leading to a low applicability of the shelter selection results. Therefore, in this study, land-use and land-cover change (LUCC) and nighttime lighting data were used to simulate population distribution and determine the number and distribution of affected people. Qualified candidate shelters were obtained based on screening criteria, and their effective capacity and accessibility information under different weather conditions were quantified. Considering factors such as population transfer efficiency, construction cost and shelter capacity constraints, a multi-objective siting model was established and solved using the non-dominated sorting genetic algorithm II (NSGA- II) to obtain the final siting scheme. The method was applied to the Dafangying Reservoir, and the results showed the following: (1) The overall mean relative error (MRE) of the population in the 35 downstream streets was 11.16 %, with good fitting accuracy. The simulation results truly reflect the population distribution. (2) Normal weather screening generated 352 qualified candidate shelters, whereas extreme rainfall weather screening generated 266 candidate shelters. (3) Based on the population distribution and weather factors, four scenarios were set up, with 63, 106, 73, and 131 shelters selected. These two factors have a significant impact on the selection of shelters and the allocation of evacuees, and should be considered in the event of a dam-failure floods.

Accurate qualitative and quantitative information on the characteristics of traffic noise exposure in densely populated urban areas is an important prerequisite for reasonable traffic noise control. The primary objective of this study is the development and application of a traffic noise exposure evaluation method based on points of interest (POIs). First, an automatic query arithmetic is used to acquire geospatial information, POIs data, building and network information from the webmap. Second, the attribute matrix of preprocessed POIs for the population is constructed. And the population distribution is obtained by principal component analysis (PCA) of POIs and Gaussian decomposition of demographic data. Then, the modified traffic noise line-source model is applied to calculate the noise distribution considering attenuation among buildings based on measured traffic flow parameters. Finally, with the help of the proposed noise evaluation indicators, and considering the noise function requirements (NFRs, which can be divided into four classes according to different area land-use types), traffic noise evaluation is realized. The proposed method is applied to a typical region with four NFR classes. It is concluded that the characteristics of traffic noise exposure are affected by traffic conditions, buildings, NFR classes and population distribution. And the crowds exposed to noise present aggregation effects, which are usually centered around specific buildings. In addition, POI types which people actives related suffer more serious noise exposure, and exposure is overestimated at low requirement regions without considering crowd distribution of the setting scenario.

Years of outbreaks of woody canker (Cryptosphaeria pullmanensis) in the United States, Iran, and China have resulted in massive economic losses to biological forests and fruit trees. However, only limited information is available on their distribution, and their habitat requirements have not been well evaluated due to a lack of research. In recent years, scientists have utilized the MaxEnt model to estimate the effect of global temperature and specific environmental conditions on species distribution. Using occurrence and high resolution ecological data, we predicted the spatiotemporal distribution of C. pullmanensis under twelve climate change scenarios by applying the MaxEnt model. We identified climatic factors, geography, soil, and land cover that shape their distribution range and determined shifts in their habitat range. Then, we measured the suitable habitat area, the ratio of change in the area of suitable habitat, the expansion and shrinkage of maps under climate change, the direction and distance of range changes from the present to the end of the twenty-first century, and the effect of environmental variables. C. pullmanensis is mostly widespread in high-suitability regions in northwestern China, the majority of Iran, Afghanistan, and Turkey, northern Chile, southwestern Argentina, and the west coast of California in the United States. Under future climatic conditions, climate changes of varied intensities favored the expansion of suitable habitats for C. pullmanensis in China. However, appropriate land areas are diminishing globally. The trend in migration is toward latitudes and elevations that are higher. The estimated area of possible suitability shifted eastward in China. The results of the present study are valuable not only for countries such as Morocco, Spain, Chile, Turkey, Kazakhstan, etc., where the infection has not yet fully spread or been established, but also for nations where the species has been discovered. Authorities should take steps to reduce greenhouse gas emissions in order to restrict the spread of C. pullmanensis. Countries with highly appropriate locations should increase their surveillance, risk assessment, and response capabilities.

Predicting the spatial distribution of species and suitable areas under global climate change could provide a reference for species conservation and long-term management strategies. Macaca thibetana and Macaca arctoides are two endangered species of Chinese macaques. However, limited information is available on their distribution, and their habitat needs lack proper assessment due to complicated taxonomy and less research attention. In recent years, scholars widely used the maximum entropy (MaxEnt) model to predict the impact of global climate and certain environmental factors on species distribution. Therefore, we used the MaxEnt model to predict the spatiotemporal distribution of both macaque species under six climate change scenarios using occurrence and high-resolution ecological data. We identified climatic factors, elevation, and land cover that shape their distribution range and determined shifts in their habitat range. The results demonstrated that temperature range, annual precipitation, forest land cover, and temperature seasonality, including the precipitation of the driest month are the main factors affecting their distribution. Currently, M. thibetana is mainly concentrated in central, eastern, southern, and southwestern China, and M. arctoides is mainly concentrated in three provinces (Yunnan, Guangxi, and Guangdong) in southern China. The MaxEnt model predicted that the suitable habitat for both species will increase with increased greenhouse emission scenarios. We also found that with the further increase in greenhouse emissions M. thibetana is expected to migrate to western China, and M. arctoides is expected to migrate to western or eastern China. This reinterpretation of the distribution of M. thibetana and M. arctoides in China, and predicted potential suitable habitat and possible migration direction, may provide new insights into the future conservation and management of these two species.