Early detection of multiple endocrine neoplasia type 1: A case report

BACKGROUND Multiple endocrine neoplasias(MENs)are a group of hereditary diseases invol-ving multiple endocrine glands,and their prevalence is low.MEN type 1(MEN1)has diverse clinical manifestations,mainly involving the parathyroid glands,gastrointestinal tract,pancreas and pituitary gland,making it easy to miss the clinical diagnosis.CASE SUMMARY We present the case of a patient in whom MEN1 was detected early.A middle-aged male with recurrent abdominal pain and diarrhea was admitted to the hos-pital.Blood tests at admission revealed hypercalcemia and hypophosphatemia,and emission computed tomography of the parathyroid glands revealed a hy-perfunctioning parathyroid lesion.Gastroscopy findings suggested a duodenal bulge and ulceration.Ultrasound endoscopy revealed a hypoechoic lesion in the duodenal bulb.Further blood tests revealed elevated levels of serum gastrin.Surgery was performed,and pathological analysis of the surgical specimens revealed a parathyroid adenoma after parathyroidectomy and a neuroendocrine tumor after duodenal bulbectomy.The time from onset to the definitive diagnosis of MEN1 was only approximately 1 year.CONCLUSION For patients who present with gastrointestinal symptoms accompanied by hyper-calcemia and hypophosphatemia,clinicians need to be alert to the possibility of MEN1.

Prospects in the application of ultrasensitive chromosomal aneuploidy detection in precancerous lesions of gastric cancer

Gastric cancer(GC)is a prevalent malignant tumor within the digestive system,with over 40%of new cases and deaths related to GC globally occurring in China.Despite advancements in treatment modalities,such as surgery supplemented by adjuvant radiotherapy or chemotherapeutic agents,the prognosis for GC remains poor.New targeted therapies and immunotherapies are currently under invest-igation,but no significant breakthroughs have been achieved.Studies have indicated that GC is a heterogeneous disease,encompassing multiple subtypes with distinct biological characteristics and roles.Consequently,personalized treatment based on clinical features,pathologic typing,and molecular typing is crucial for the diagnosis and management of precancerous lesions of gastric cancer(PLGC).Current research has categorized GC into four subtypes:Epstein-Barr virus-positive,microsatellite instability,genome stability,and chromosome instability(CIN).Technologies such as multi-omics analysis and gene sequencing are being employed to identify more suitable novel testing methods in these areas.Among these,ultrasensitive chromosomal aneuploidy detection(UCAD)can detect CIN at a genome-wide level in subjects using low-depth whole genome sequencing technology,in conjunction with bioinformatics analysis,to achieve qualitative and quantitative detection of chromosomal stability.This editorial reviews recent research advancements in UCAD technology for the diagnosis and management of PLGC.

Annoyance-type speech emotion detection in working environment

In order to recognize people＇s annoyance emotions in the working environment and evaluate emotional well- being, emotional speech in a work environment is induced to obtain adequate samples of emotional speech, and a Mandarin database with two thousands samples is built. In searching for annoyance-type emotion features, the prosodic feature and the voice quality feature parameters of the emotional statements are extracted first. Then an improved back propagation （BP） neural network based on the shuffled frog leaping algorithm （SFLA） is proposed to recognize the emotion. The recognition capability of the BP, radical basis function （RBF） and the SFLA neural networks are compared experimentally. The results show that the recognition ratio of the SFLA neural network is 4. 7% better than that of the BP neural network and 4. 3% better than that of the RBF neural network. The experimental results demonstrate that the random initial data trained by the SFLA can optimize the connection weights and thresholds of the neural network, speed up the convergence and improve the recognition rate.

Application of SPAC method and electromagnetic wave CT in karst detection of Wuhan Metro Line 8

In recent years,karst construction projects in the built-up area of Wuhan(capital of Hubei Province,China)are increasing,and the karst geological disasters have aroused social concerns.The actual engineering projects usually use shallow geophysical exploration methods to explore karst.This paper uses Spatial Auto-Correlation Method(SPAC)and electromagnetic Computerized Tomography(CT)to detect karst in urban built-up areas.Depending on the different physical properties of rock and soil,the SPAC method can better reveal the interface between soil and rock strata and the interface between soil layers.The electromagnetic CT method can identify strata according to the apparent absorption coefficient,which can better reveal the interface between soil and rock,the interface between the more intact and weathered rock.The SPAC method is mainly qualitative to measure the low-speed area,namely,the wrong geological body i.e.,karst cave,but also can detect the fracture zone or filling mode of karst cave,and at the same time,cannot use exploration holes or logging observation.The electromagnetic CT method can accurately detect the location and scale of the karst caves and has a higher accuracy detecting karst bands.In addition,exploration holes or well logging observations are also expected to be conducted,and their detection effect is greatly affected by lithology.

A Wipe Transition Detection Approach Using Macroblock Type Information for MPEG Videos

A new wipe transition detection approach was proposed. By analyzing the spatial-temporal characteristics of an ideal wipe production model, the concept of wipe transition strip (TS) was introduced. The macroblock type information of P-frames is used to extract TS regions. An improved TS region accumulation technique is performed for detecting and verifying wipe transitions. The experimental results indicate that the proposed approach is capable of detecting various wipe transitions quickly and accurately.

Improving early diagnosis of multiple endocrine neoplasia type 1 by assessing the gastrointestinal symptoms,hypercalcemia,and elevated serum gastrin

Despite advancements in the field,early diagnosis of multiple endocrine neoplasia type 1(MEN1)remains unachievable.This letter to the editor highlighted the importance of carefully assessing gastrointestinal symptoms,hypercalcemia,and elevated serum gastrin levels,as suggested by Yuan et al in their paper.They focused on a patient with recurrent abdominal pain and diarrhea whose diagnostic path led to establishing a MEN1 diagnosis within a year.This emphasized the need for clinicians to consider MEN1 in patients with similar presentations,particularly when gastrointestinal symptoms persist or recur after discontinuation of proton pump inhibitors,especially knowing that early recognition and intervention are crucial for improving patient outcomes.

Development of RT PCR Assay for Detection of Duck Hepatitis Virus Type 1

In this study,a RT-PCR assay for rapid detection of duck hepatitis virus type 1( DHV-1) was established in the presence of a pair of primers designed based on vp1 gene sequence,using the genomic RNA of DHV-1 or other common viruses as the template. The template was serially diluted 10-fold to determine the reaction sensitivity. Finally,seven liver samples of ducks with suspected DHV-1 infection,which were collected from different regions of Jiangsu Province,were detected with this method. The results showed that a DNA fragment of about 360 bp was specifically amplified with the RT-PCR system,and the detection limit was1 fg/μL. The detection rate of clinical samples with this method was 100%. The results revealed that the RT-PCR system which had high specificity and high sensitivity in the detection of DHV-1 was successfully established.

Common Transceiver LIF⁃Lidar Based on Y⁃Type Optical Fiber for Marine Oil Spill Detection

This paper presents a novel laser⁃induced fluorescence(LIF)Lidar system for marine oil spilling detection.A bifurcated Y⁃type optical fiber and an optical collimating lens compose a coaxial configuration transceiver for this LIF⁃Lidar system.This LIF⁃Lidar system was further applied to measure the excitation spectra from floating oil slicks with different thicknesses on top of seawater at different distances.The system presents several advantages such as compact structure,stable optical path,and convenient operation,which offers a wide application prospect in ocean exploration.

Consistency Analysis of Detection Results of Two Herpes Simplex Virus (HSV) Type II Nucleic Acid Detection Kits

Objective: The objective of the study is to verify the clinical validity of the following kits with the comparative experimental analysis and evaluate whether their performance can meet the clinical requirements, i.e. Class III in vitro diagnostic reagent “Herpes Simplex Virus (HSV) Type II Nucleic Acid Detection Kit (PCR-Fluorescence Probe Method)” of Daan Gene Co., Ltd. (Daan kit for short) and “Herpes Simplex Virus (HSV) Type II Nucleic Acid Detection Kit (Fluorescence PCR Method)” of Wuhan Biot Gene Co., Ltd. (Biot kit for short). Method: In the study process, the samples were divided into positive and negative groups according to the control test results, and the clinical application performance of Daan kit and Biot kit was evaluated by comparing their test results. Results: The results show that two kits indicate the same test results, i.e. 26 positive and 107 negative samples in a total of 133 male urethral discharge samples, and 32 positive and 238 negative samples in a total of 270 female cervical secretion samples. Conclusion: It can be concluded from the clinical test that Daan and Biot Herpes Simplex Virus (HSV) Type II Nuc- leic Acid Test Kits are reliable, accurate, safe, convenient for use, stable and high-value in the clinical application.

Detection and significance of blood rheology and coagulation function index in elderly patients with type 2 diabetes mellitus complicated with cerebral infarction

Objective: To investigate the level of blood rheology and coagulation function in elderly patients with type 2 diabetes mellitus (T2DM) and cerebral infarction and its significance. Methods: A total of 81 elderly patients with T2DM and cerebral infarction were selected as the observation group, 80 cases of T2DM patients without cerebral infarction were selected as T2DM group, and 80 healthy elderly people as control group. According to the Adama classification, the patients in the observation group were divided into three groups: lacunar infarction group (n=28), small infarction group (n=39) and large infarction group (n=14). The blood rheology and coagulation function indexes levels among the groups were compared. Results: The single factor variance analysis showed that the differences of the high shear whole blood viscosity, plasma viscosity, low shear whole blood viscosity, APTT, PT, FIB and D-D levels among the control group were significant, T2DM group and observation group were statistically significant. Compared with the control group, the high shear whole blood viscosity, plasma viscosity, low shear whole blood viscosity, FIB and D-D levels in the T2DM group and observation group were significantly increased, PT and APTT were decreased sharply, and in the observation group high shear whole blood viscosity, plasma viscosity, low shear whole blood viscosity, FIB and D-D levels were significantly higher than that of T2DM group APTT, and PT were significantly lower than those of T2DM group. Lacunar infarction group, small infarction group and large infarction group with increased infarct size, with high shear whole blood viscosity, plasma viscosity, low shear whole blood viscosity, FIB and D-D levels were significantly increased, while APTT and PT were significantly decreased. Conclusion: T2DM and cerebral infarction patients with abnormal blood rheology and coagulation function, the index examination has important clinical value for cerebral infarction area evaluation.

In-Line Inspection of Pipeline Defects Detection Using Ring-Type Laser

Pipeline plays a vital role in transporting fluids like oils, water, and petrochemical substances for longer distances. Based on the materials they carry, prolonged usage may cause the initiation of defects in the pipeline. These defects occur due to the formed salt deposits, chemical reaction happens between the inner surface and the transferring substance, prevailing environmental conditions, etc. These defects, if not identified earlier may lead to significant losses to the industry. In this work, an in-line inspection system utilizes the nondestructive way for analyzing the internal defects in the petrochemical pipeline. This system consists of a pipeline inspection robot having two major units namely the visual inspection unit and the power carrier unit. The visual inspection unit makes use of a ring-type laser diode and the camera. The laser diode serves as a light source for capturing good quality images of inspection. This unit is controlled by the Arduino in the power carrier unit which provides the necessary movement throughout the pipe. The inspected images captured by the camera are further processed with the aid of NI vision assistant software. After applying the processing function parameters provided by this software, the defect location can be clearly visualized with high precision. Three sets of defects are introduced in a Polylactide (PLA) pipe based on its position and angle along the circumference of the pipe. Further, this robot system serves as a real-time interactive image synchronization system for acquiring the inspected images. By comparing the actual and calculated defect size, the error percentage obtained was less than 5%.

A Machine Learning-based Cloud Detection Algorithm for the Himawari-8 Spectral Image

Cloud Masking is one of the most essential products for satellite remote sensing and downstream applications.This study develops machine learning-based(ML-based)cloud detection algorithms using spectral observations for the Advanced Himawari Imager(AHI)onboard the Himawari-8 geostationary satellite.Collocated active observations from Cloud-Aerosol Lidar with Orthogonal Polarization(CALIOP)are used to provide reference labels for model development and validation.We introduce both daytime and nighttime algorithms that differ according to whether solar band observations are included,and the artificial neural network(ANN)and random forest(RF)techniques are adopted for comparison.To eliminate the influences of surface conditions on cloud detection,we introduce three models with different treatments of the surface.Instead of developing independent ML-based algorithms,we add surface variables in a binary way that enhances the ML-based algorithm accuracy by~5%.Validated against CALIOP observations,we find that our daytime RF-based algorithm outperforms the AHI operational algorithm by improving the accuracy of cloudy pixel detection by~5%,while at the same time,reducing misjudgment by~3%.The nighttime model with only infrared observations is also slightly better than the AHI operational product but may tend to overestimate cloudy pixels.Overall,our ML-based algorithms can serve as a reliable method to provide cloud mask results for both daytime and nighttime AHI observations.We furthermore suggest treating the surface with a set of independent variables for future ML-based algorithm development.

Algorithmic Scheme for Concurrent Detection and Classification of Printed Circuit Board Defects

An ideal printed circuit board(PCB)defect inspection system can detect defects and classify PCB defect types.Existing defect inspection technologies can identify defects but fail to classify all PCB defect types.This research thus proposes an algorithmic scheme that can detect and categorize all 14-known PCB defect types.In the proposed algorithmic scheme,fuzzy cmeans clustering is used for image segmentation via image subtraction prior to defect detection.Arithmetic and logic operations,the circle hough transform(CHT),morphological reconstruction(MR),and connected component labeling(CCL)are used in defect classification.The algorithmic scheme achieves 100%defect detection and 99.05%defect classification accuracies.The novelty of this research lies in the concurrent use of CHT,MR,and CCL algorithms to accurately detect and classify all 14-known PCB defect types and determine the defect characteristics such as the location,area,and nature of defects.This information is helpful in electronic parts manufacturing for finding the root causes of PCB defects and appropriately adjusting the manufacturing process.Moreover,the algorithmic scheme can be integrated into machine vision to streamline the manufacturing process,improve the PCB quality,and lower the production cost.

An ELISA Based on a Truncated Soluble ORF2 Protein for the Detection of PCV2 Antibodies in Domestic Pigs

Postweaning multisystemic wasting syndrome (PMWS) is an important swine disease that is closely associated with porcine circovirus type 2 (PCV2). The capsid protein (Cap protein) is a major structural protein that has at least three immunoreactive regions, and it can be a suitable candidate antigen for detecting the specific antibodies of a PCV2 infection. In the present study, an indirect enzyme-linked immunosorbent assay (TcELISA) based on a truncated soluble Cap protein produced in Escherichia coli (E.coli) was established and validated for the diagnostic PCV2 antibodies in swine. The TcELISA was validated by comparison with an indirect immunofluorescence assay (IIFA). The diagnostic sensitivity (DSN), specificity (DSP), and accuracy of the TcELISA were 88.6%, 90.7% and 89.4%, respectively. The agreement rate was 89.38% between results obtained with TcELISA and IIFA on 113 field sera. A cross-reactivity assay showed that the method was PCV2-specific by comparison with other sera of viral disease. Therefore ,the TcELISA will be helpful for the development of a reliable serology diagnostic test for large scale detection of PCV2 antibodies and for the evaluation of vaccine against PCV2 in swine.

Sparse Reduced-Rank Regression with Outlier Detection

Based on the multivariate mean-shift regression model,we propose a new sparse reduced-rank regression approach to achieve low-rank sparse estimation and outlier detection simultaneously.A sparse mean-shift matrix is introduced in the model to indicate outliers.The rank constraint and the group-lasso type penalty for the coefficient matrix encourage the low-rank row sparse structure of coefficient matrix and help to achieve dimension reduction and variable selection.An algorithm is developed for solving our problem.In our simulation and real-data application,our new method shows competitive performance compared to other methods.

Sensitivity and Specificity Analysis Relation to Statistical Hypothesis Testing and Its Errors: Application to Cryptosporidium Detection Techniques

The use of Statistical Hypothesis Testing procedure to determine type I and type II errors was linked to the measurement of sensitivity and specificity in clinical trial test and experimental pathogen detection techniques. A theoretical analysis of establishing these types of errors was made and compared to determination of False Positive, False Negative, True Positive and True Negative. Experimental laboratory detection methods used to detect Cryptosporidium spp. were used to highlight the relationship between hypothesis testing, sensitivity, specificity and predicted values. The study finds that, sensitivity and specificity for the two laboratory methods used for Cryptosporidium detection were low hence lowering the probability of detecting a “false null hypothesis” for the presence of cryptosporidium in the water samples using either Microscopic or PCR. Nevertheless, both procedures for cryptosporidium detection had higher “true negatives” increasing its probability of failing to reject a “true null hypothesis” with specificity of 1.00 for both Microscopic and PCR laboratory detection methods.

DETECTION OF KNOWN SIGNALS IN 1/f FRACTAL NOISE

Based on the whitening property of wavelet transformation for 1/f noise, this paper addresses the problem of detecting deterministic signals in the presence of 1/f fractal noise. The transfer function of whitening filter is provided as well as the condition for whitening. The receiver structure based on Karhunen-Loeve expansion and the decision rule are also given. Finally performance of the detector is analyzed.

抗PCV4 Cap蛋白抗体间接ELISA检测方法的建立

为建立可应用于猪圆环病毒4型(PCV4)候选疫苗特异性抗体检测与评价方法,本研究应用PCV4 Cap蛋白作为抗原,以PCV4多克隆兔源抗体作为一抗,优化各反应的最佳条件并建立了针对PCV4 Cap蛋白抗体的间接ELISA方法。最佳条件为2μg/m L PCV4 Cap纯化蛋白,4℃包被过夜,5%脱脂乳封闭60 min,待检血清稀释比例为1∶800,反应条件为37℃、45 min,酶标抗体稀释比例为1∶5000,反应条件为37℃、60 min,底物显色时间为10 min,Cut of f值为0.157,灵敏度可达102400倍。成功建立的抗PCV4Cap蛋白抗体间接ELISA检测方法具有良好的敏感性、重复性和特异性。可为检测PCV4候选疫苗的特异性抗体水平提供一种精准、高效的方法。

HbA1c、LDL-C、HDL-C联合检测在2型糖尿病肾病中的诊断价值

目的:探究糖化血红蛋白(HbA1c)、低密度脂蛋白胆固醇(LDL-C)、高密度脂蛋白胆固醇(HDL-C)联合检测在2型糖尿病肾病中的诊断价值。方法:选取2019年1月—2021年12月南京中医药大学附属苏州市中医医院收治的120例2型糖尿病患者作为研究对象。根据患者是否发生糖尿病肾病将其分为合并肾病组(n=35)和未合并肾病组(n=85)。收集两组患者一般资料。检测两组Hb A1c、LDL-C、HDL-C。比较两组一般资料及Hb A1c、LDL-C、HDL-C水平。分析2型糖尿病肾病的危险因素。分析HbA1c、LDL-C、HDL-C对2型糖尿病肾病的诊断价值。结果:合并肾病组糖尿病病程长于未合并肾病组,吸烟史占比高于未合并肾病组,差异有统计学意义(P<0.05)。合并肾病组HbA1c、LDL-C水平均高于未合并肾病组,HDL-C水平低于未合并肾病组,差异有统计学意义(P<0.05)。logistic分析结果显示,HbA1c、LDL-C、吸烟史、糖尿病病程均是2型糖尿病患者合并糖尿病肾病的危险因素,HDL-C是保护因素(P<0.05)。HbA1c、LDL-C、HDL-C联合检测的AUC最高。结论:HbA1c、LDL-C、HDL-C联合检测应用于2型糖尿病肾病诊断中,具有较高的诊断价值,为临床对2型糖尿病肾病的早期诊断提供新思路。