Subjects: Medicine, Pharmacy >> Clinical Medicine submitted time 2024-04-24 Cooperative journals: 《中国全科医学》
Abstract： Background As revealed by previous studies，the head shaking tilt suppression test （HSTST）is associated with the vestibular cerebellum-mediated central storage mechanism and the video head impulse test（vHIT）is crucial for the diagnosis of vestibular diseases. Objective To explore the clinical application value of HSTST and vHIT in vestibular migraine（VM）and Meniere's disease（MD）. Methods Patients presenting with vertigo or dizziness as the primary complaint and diagnosed with VM and MD were selected from the Neurology Department of the Second People's Hospital of Guiyang from July 2021 to December 2022. After collecting their medical history and performing bedside examinations，pure tone audiometry test was conducted on those with hearing impairment. All patients completed vestibular function tests，including head shaking test （HST），HSTST，caloric test，and vHIT，were performed，followed by calculating the tilt suppression index（TSI）. Thenthe Clinical features and examination results of VM and MD patients with HST positive were compared，and the ROC curve of TSI was plotted to distinguish between the two groups of patients. Results Among the 50 VM patients involved in the study，22（44.0%） were HST positive，including 19（86.4%）exhibiting horizontal nystagmus and 3（13.6%）showing vertical nystagmus. Among the 45 MD patients，23（51.1%）were HST positive，all of whom were horizontal nystagmus. The analysis of the patients with HST positive showed that the female to male ratio in VM and MD patients was 4.5:1 and 1:1.3，respectively. The prevalence of family history of headaches was higher in VM patients compared to MD patients（P<0.05）. VM patients exhibited lower proportions of vomiting，tinnitus，ear tightness，and hearing loss symptoms（31.8%，18.2%，13.6%，13.6%）compared to MD patients（73.9%，100%，82.6%，100%），with a higher proportion of accompanying headache symptoms（77.3%） than MD patients（8.7%）（P<0.05）. Pure tone audiometry revealed a higher hearing loss rate in MD patients compared to VM patients（P<0.001）. Significant differences were observed in vHIT between VM and MD patients（P<0.05）. Then the TSI differed significantly between VM and MD patients ［（25.41±12.15）% and（78.71±13.76）%，respectively］（P<0.05）. From ROC curves，the area under the curve（AUC）was 0.962（95%CI=0.91-1.00）with a cut-off point at 0.66（sensitivity=0.90， specificity=0.95）. Conclusion Vestibular migraine primarily involves a central mechanism，and HSTST combined with vHIT can be used as auxiliary examination tools to differentiate diagnosis between VM and MD.
submitted time 2024-04-03 Cooperative journals: 《农业图书情报学报》
Abstract： [Purpose/Significance] Geographical indications (GIs) are an important tool for local governments in China to carry out brand building of agricultural products. Brand management is a continuous systematic project involving multiple subjects. Among them, the problem of government policy attention in the field of brand management of agricultural products with GIs deserves in-depth study. This paper aims to construct a policy attention analysis model in the field of brand management of GI agricultural products based on natural language processing technology. This model provides technical support for local governments to explore the status quo of local GI agricultural products' brand management, analyze the distribution of policy attention, and assist in optimizing strategies to promote their products' brand development. [Method/Process] The study is focused on the distribution of attention paths of GI agricultural products' brand management policies from the perspective of the local government: an analysis model of brand management policies of GI agricultural products was constructed in order to support the local government to carry out the analysis of the status quo of local agricultural products' brand management and policy optimization, and provide decision-making support for the optimization of brand management measures of the local agricultural products. First, this paper built a basic corpus based on the Python crawler technology, collected authoritative public information on the Internet, utilized the domain dictionary and UIE general information extraction framework to extract the text of management measures published in local government policies, and built a database of brand management measures of GI agricultural product. Second, a classification model of brand management measures of GI agricultural products based on the Transformer model was constructed. Third, this paper built a classification model based on the Transformer model, which can classify the extracted brand management measures of agricultural products and construct the policy attention distribution map. Finally, based on the policy attention distri-bution given by the model, we can find the brand management bottlenecks and recommend countermeasures to solve the bottlenecks. [Results/Conclusions] This paper takes Yantai apples as an example for model validation. After extracting and categorizing Yantai apples' brand management data, it is found that the policy attention of Yantai apples is more con-centrated, and the measures are highly similar, with 41.1% of the text of the measures focused on the part of brand positioning and planning, 31.7% on the part of brand competitiveness enhancement, and less than 10% on the part of brand marketing and protection. It can be seen that the brand effect of Yantai apples with GIs has not been well utilized.
Subjects: Medicine, Pharmacy >> Clinical Medicine submitted time 2024-02-27 Cooperative journals: 《中国全科医学》
Abstract： Background Locally advanced gastric cancer mainly includes stage Ⅲ gastric cancer，which is mainly treated with comprehensive therapy. Postoperative recurrence is a key factor affecting the prognosis of patients. Objective To explore the influencing factors of long-term prognosis in patients with stage Ⅲ gastric cancer undergoing D2 radical surgery and adjuvant chemotherapy. Methods Gastric cancer patients who underwent D2 radical surgery and adjuvant chemoradiotherapy were collected from the Department of Radiotherapy at Zhongshan Hospital affiliated to Fudan University from January 2009 to December 2014. They were pathologically diagnosed with stage Ⅲ gastric cancer according to the International Union of Cancer （UICC）and American Cancer Federation（AJCC）8th edition TNM staging system for gastric cancer. All postoperative patients were followed up every 3 months in the first year，every 6 months for the following 2 years，and once a year thereafter. The deadline for follow-up is December 15，2021. Survival rates of subgroups were compared using Log-rank tests.The influencing factors of overall survival（OS）and disease-free survival（DFS）were compared using Cox proportional hazards regression analysis，and the prediction of clinicopathological features were analyzed by Nomogram. Comparison of survival differences among patients with different pTNM stagings，age，metastatic lymph node radios（LNR），and gastrectomy methods using Kaplan Meier method. Results A total of 135 qualified patients were included，with a median follow-up time of 10.48 years. Within 5 years，there were 70 cases of recurrence and 62 deaths. The 5-year DFS rate and OS rate were 48.1%（65/135）and 54.1%（73/135），respectively； Within 10 years，there were 74 cases of recurrence and 74 deaths. The 10-year DFS rate nd OS rate were both 45.2%. The log-rank test results showed that there was a statistically significant difference in 5-year survival rates among patients with different pTNM stagings，pT stagings，LNRs，cancer nodules，tumor locations，and gastrectomy methods（P<0.05）. The 10-year survival rates of patients with different pTNM stagings，pT stagings，LNRs，nerve infiltrations，and gastrectomy methods were compared，and the differences were statistically significant（P<0.05）. The results of multivariate Cox proportional hazards regression analysis showed that pTNM staging（Stage Ⅲ A，OS：HR=0.40，95%CI=0.19~0.83； DFS：HR=0.40，95%CI=0.19~0.92），LNR（>50%，OS：HR=1.74，95%CI=1.03~2.94； DFS：HR=1.87，95%CI=1.73~1.02），and gastrectomy method（total gastrectomy，OS：HR=2.07，95%CI=1.22~3.50； DFS：HR=2.02，95%CI=1.20~3.41）were independent influencing factors for OS and DFS in patients with stage Ⅲ gastric cancer undergoing D2 radical surgery with adjuvant chemotherapy（P<0.05），while age（ ≤ 40 years，HR=2.19，95%CI=1.06~4.53）was an independent influencing factor for OS. Moreover，nomogram indicated that age，pTNM staging，LNR，and gastrectomy method have good predictive effects on the prognosis. For recurrence，10 cases（7.4%）experienced local recurrence（recurrence of anastomotic sites and lymph nodes within the radiation field），35 cases（25.9%）experienced abdominal and pelvic dissemination of implants，and 37 cases（27.4%）experienced distant metastasis（including lung，liver，bone，brain and other organs）； Some patients had two or more types of recurrence. The postoperative survival curves of stage Ⅲ gastric cancer patients with different pTNM stagings，age，LNRs，and gastrectomy methods were compared，and the differences were statistically significant（P<0.05）. Conclusion Most patients with stage Ⅲ gastric cancer who undergo adjuvant chemoradiotherapy after D2 radical surgery experience recurrence or death within 5 years. pTNM staging，LNR，and gastrectomy method are factors that affect the prognosis of these patients.
Subjects: Other Disciplines >> Synthetic discipline submitted time 2023-03-31 Cooperative journals: 《农业图书情报学报》
Abstract： [Purpose/Significance] Advances in single-cell sequencing and high-throughput technology have made it possible for plant genomics to accumulate large quantities of data describing multidimensional genomic-wide molecular phenotypes at low cost. As powerful data mining tools, deep learning techniques can be utilized to further predict and interpret the acquired molecular phenotypes. In recent studies, deep learning has been shown to yield significant results in plant genomics and crop breeding research. However, a complete review of deep learning applications in plant genomics is lacking. [Method/Process] The input to deep learning applied to genomics is usually biological sequences and molecular phenotypes as predictor and target variables, respectively. We introduced the workflow from four views: input data pre-processing includes retrieval, coding, and splitting; model construction and training includes the selection of model architecture and hyperparameters; model evaluation and interpretability. Specifically, this paper introduces the background of deep learning approaches, including the latest graph neural networks; then it discusses two prominent issues in the intersection of genomics and deep learning with respect to gene characterization and protein characterization: 1) how to model the flow of information from plant genomic DNA sequences to molecular phenotypes; and 2) how deep learning models can be utilized to identify functional variation in natural populations? Specifically, the paper summarizes the current status of deep learning applications in related fields, which include deep learning and DNA and gene characterization research, interpretability of deep learning in genomics applications, graph neural networks in genomics, deep learning and genomic variation research, deep learning in protein prediction, ALPHAFOLD in protein prediction, deep learning and crop breeding research, and unsupervised learning in genomics and protein characterization. [Results/Conclusions] This article summarizes how traditional deep-learning algorithms, graph deep-learning, generative adversarial networks and interpretable AI are applied in current research in order to address these two problems. Finally, the prospects for deep learning in future plant genomics research and crop improvement are discussed. Overall, deep learning has provided better results than conventional methods in many genomics research directions, and the application of deep learning in genomics has yielded early applications of scientific and economic significance. Deep learning offers two distinct advantages: 1) end-to-end learning, with the ability to integrate multiple pre-processing steps into a single model; and 2) multimodal data processing capabilities that can handle extremely heterogeneous data in genomics. The advancement of deep learning has the potential to expand new research perspectives in genomics and crop breeding, and to facilitate larger-scale association studies in both phenotypic and genotypic genomics as algorithms become more accurate.
Subjects: Medicine, Pharmacy >> Clinical Medicine submitted time 2023-03-31 Cooperative journals: 《中国全科医学》
Abstract： Background Early diagnosis of gastric cancer is essential for patient prognosis. Currently，endoscopic forceps biopsy（EFB） is an important tool for the diagnosis of gastric cancer. However，it has been shown in relevant studies that there are some differences between EFB-based diagnosis and pathological diagnosis after endoscopic submucosal dissection（ESD），resulting in an underestimation of the patient's condition. No related research has been conducted in northern Shaanxi. Objective To calculate the rate of pathological upgrading in gastric mucosal lesions after ESD in five hospitals in northern Shaanxi，and to analyze the factors associated with pathological upgrading. Methods We recruited patients with gastric mucosal lesions who underwent ESD following EFB in five hospitals（Yan'an University Affiliated Hospital，Yan'an People's Hospital，The First Hospital of Yulin，Yan'an Traditional Chinese Medicine Hospital，Zichang People's Hospital） from January 1，2016 to December 30，2021. We classified the pathological results of gastric mucosal lesions into the following categories：chronic gastric inflammatory changes（CIC），low-grade gastric intraepithelial neoplasia（LGIN），high-grade gastric intraepithelial neoplasia（HGIN），early gastric cancer（EGC） and progressive gastric cancer. The difference between EFBbased diagnosis and pathological diagnosis of ESD specimens was analyzed. Pathological upgrading was defined as progression in pathological results. The pathological upgrading in patients with CIC，LGIN or HGIN was counted. The factors associated with pathological upgrading were analyzed. Results A total of 241 patients were included. Seventy-six（31.5%） were found with pathological upgrading after ESD compared with their EFB-based diagnoses. Binary logistic regression analysis showed that endoscopic classification〔 OR=0.134，95%CI（0.029，0.617）〕 and superficial ulceration〔 OR=3.595，95%CI（1.226，10.536）〕 were associated with pathological upgrading in CIC（ P<0.05）. Age〔 OR=3.961，95%CI（1.071，14.650）〕，endoscopic classification〔 OR=0.311，95%CI（0.127，0.765）〕，redness of mucosal surface〔 OR=5.830，95%CI（1.591， 21.355）〕，and number of specimens〔 OR=0.234，95%CI（0.063，0.872）〕 were associated with pathological upgrading in LHIN（ P<0.05）. Lesion size〔 OR=3.143，95%CI （1.003，9.852）〕 was associated with pathological upgrading in HGIN（ P<0.05）.Conclusion Medical workers should be alert to the potential possibility of underestimated pathology in EFB if the lesion is CIC suggested by EFB but is endoscopically classified as flat or concave with surface ulceration. And the potential possibility is also should be considered if there is only one biopsy specimen obtained from a patient aged greater than 60 years，and the lesion is LGIN suggested by EFB，but is endoscopically classified as flat with redness of mucosal surface，and an ESD can be underwent if necessary. Moreover，if a lesion greater than 2 cm in size is HGIN suggested by EFB，which is probably EGC，and an ESD is recommended to verify it.
Subjects: Medicine, Pharmacy >> Clinical Medicine submitted time 2023-01-28 Cooperative journals: 《中国全科医学》
Abstract：
Objective To investigate the pathological upgrading rate of gastric mucosal lesions after endoscopic submucosal dissection in five hospitals in Northern Shaanxi, and to analyze the related factors of pathological upgrading. Methods the data of patients with gastric mucosal lesions who received ESD treatment in five hospitals from January 1, 2016 to December 30, 2021 were retrospectively analyzed, the pathological escalation rate was calculated, and the related factors of pathological escalation were analyzed by statistical methods. Results of the 241 cases collected this time, the pathological escalation rate was 31.54% in ESD group and 32.14% in CIC group，endoscopic classification (OR:0.134, CI:0.029-0.617) and surface ulcer (OR:3.596, CI:1.226-10.536) were related to pathological escalation; The pathological upgrading rate of LGIN group was 32%,age (0R:3.961, CI:1.071-14.650), endoscopic typing (OR:0.331, CI:0.127-0.765), redness of surface (OR:5.830, CI:1.591-21.355) and the number of samples taken (OR:234, CI:0.063-0.872) were related to its pathological upgrading; The pathological upgrading rate of HGIN group was 38.46%, and the size of lesion (OR:3.143, CI:1.003-9.852) was an independent related factor of pathological upgrading. Conclusion If the preoperative biopsy is suggestive of CIC, but the lesions are endoscopically classified as flat or concave with surface ulceration, they should be alert to the possibility that the pathology is underestimated; The preoperative biopsy was suggestive of LGIN, but when the patient was aged > 60 years, the lesion was flat type, the surface of the lesion was red and only 1 block was taken for biopsy, it was not excluded that the preoperative pathology was underestimated and ESD was feasible if necessary; With lesion size > 2cm, the lesion diagnosed as HGIN by preoperative biopsy was likely EGC, and ESD was recommended.
Subjects: Psychology >> Psychological Measurement submitted time 2021-12-14
Abstract： Forced-choice (FC) test is widely used in non-cognitive tests because it can control the response bias caused by the traditional Likert method, while traditional scoring of forced-choice test produces ipsative data that has been criticized for being unsuitable for inter-individual comparisons. In recent years, the development of multiple forced-choice IRT models that allow researchers to obtain normative information from forced-choice test has re-ignited the interest of researchers and practitioners in forced-choice IRT models. First, the six prevailing forced-choice IRT models are classified and introduced according to the adopted decision models and item response models. Then, the models are compared and summarized from two perspectives: model construction ideology and parameter estimation methods. Next, it reviews the applied research of the model in three aspects: parameter invariance testing, computerized adaptive testing (CAT) and validity study. Finally, it is suggested that future research can move forward in four directions: model expansion, parameter invariance testing, forced-choice CAT, and validity research. "
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