Nucleic acid-based molecular diagnostic methods are considered the gold standard for detecting infectious pathogens.However,when applied to portable or on-site rapid diagnostics,they still face various limitations and challenges,such as poor specificity,cumbersome operation,and portability difficulties.The CRISPR(Clustered regularly interspaced short palindromic repeats)/CRISPR-associated protein(Cas)-fluorescence detection method holds the potential to significantly enhance the specificity and signal-to-noise ratio of nucleic acid detection.In this study,we developed a portable grayscale reader detection system based on loop-mediated isothermal amplification(LAMP)-CRISPR/Cas.On one hand,in the presence of CRISPR RNA(crRNA),the CRISPR/Cas12a system was employed to achieve precise fluorescent detection of self-designed LAMP amplification reactions for influenza A and influenza B viruses.This further validated the high selectivity and versatility of the CRISPR/Cas system.On the other hand,the accompanying independently developed portable grayscale reader allowed for low-cost collection of fluorescence signals and high-reliability visual interpretation.At the end of the detection process,it directly provided positive or negative results.Practical sample analyses using this detection system have verified its reliability and utility,demonstrating that this system can achieve highly sensitive and highly specific portable analysis of influenza viruses.

Ductal carcinoma in situ of the breast (DCIS) most commonly manifests as asymptomatic calcifications at mammography. The most common manifestation of MRI is nonmass enhancement. The ultrasound mainly presents as a hypoechoic irregular hypervascular mass without posterior features. Core-needle biopsy is a commonly used method for preoperative diagnosis of DCIS. Due to differences in needle type and sample size, there is a certain degree of pathological upgrading of the lesion. In recent years, there has been controversy over the diagnosis and treatment of DCIS. With the development of breast disease diagnostic technology, advances in digital breast tomography, artificial intelligence, and radiomics are expected to help DCIS management and address issues such as overdiagnosis.

Objective To observe the regulatory mechanism of drug-containing serum of Jinghou Zengzhi Prescription based on qi and blood replenishing method on the expression of growth and differentiation factor 9(GDF9)and apoptosis of ovarian granulosa cells in rats with controlled ovarian hyperstimulation(COH).Methods Serum of COH rats(blank serum)and serum of COH rats gavaged by the Jinghou Zengzhi Prescription were prepared.A COH rat model was established and ovarian granulosa cells were collected.The experiment was divided into 5 groups:blank serum group,drug-containing serum group,drug-containing serum+SB203580[p38 mitogen-activated protein kinase(p38MAPK)inhibitor]group,drug-containing serum + PDTC[nuclear transcription factor κB(NF-κB)inhibitor]group,drug-containing serum + SB203580 + PDTC group.The mRNA expression levels of p38MAPK,casein kinase 2(CK2),nuclear transcription factor κB inhibitor α(IκBα),NF-κB and GDF9 were detected by real-time quantitative polymerase chain reaction(qRT-PCR),and GDF9 protein expression level was detected by Western Blot,and ovarian granulosa cell apoptosis was detected by terminal-deoxynucleoitidyl transferase mediated nick end labeling(TUNEL).Results The drug-containing serum of Jinghou Zengzhi Prescription decreased the mRNA expressions of p38MAPK and NF-κB,elevated the mRNA expressions of CK2 and IκBα,increased the mRNA and protein expression levels of GDF9,and decreased the apoptosis rate of ovarian granulosa cells in COH rats.The addition of p38MAPK inhibitor SB203580 alone and the addition of NF-κB inhibitor PDTC alone both promoted the mRNA and protein expressions of GDF9 and reduced the apoptosis rate of granulosa cells.Conclusion The drug-containing serum of Jinghou Zengzhi Prescription based on qi and blood replenishing method can promote the expression of GDF9 and inhibit the apoptosis of ovarian granulosa cells in rats with COH,and its mechanism may be related to the regulation of the expression of genes of the dual signaling pathways of p38MAPK and NF-κB.

Objective We aim to analyse semaglutide related adverse events in real-world,overall and by gender and age subgroups and compare the differences of different gender and age patients in adverse events,in order to supply references for security usage in the clinic.Methods OpenVigil 2.1 was used to search FDA Adverse Event Reporting System for semaglutide related adverse events from the establishment of the databases to April 2023.According to age and gender,patients were divided into 18-64 years old group and≥65 years old group,male group and female group.We selected ten adverse events which we interested(nausea,diarrhoea,vomiting,pancreatitis,cholecystitis,cholelithiasis,hypoglycaemia,diabetic retinopathy,acute kidney injury and thyroid cancer/medullary thyroid cancer)and analyzed overall and each group of semaglutide adverse events.Results A total of 5 330 cases and 15 558 adverse events were collected.2 935 patients aged 18-64 old group years with 8 553 adverse events;2 395 patients aged≥65 years old group with 7 005 adverse events.2 231 male group patients with 6 195 adverse events;3 059 female group patients with 9 277 adverse events.The sex of 40 patients was unknown.Nausea(1 089 cases/7.00％),vomiting(775 cases/4.98％)and diarrhoea(545 cases/3.50％)remained the most common adverse events.The constituent ratio of pancreatitis was significantly higher in patients aged 18-64 years old group than in patients aged 65 years old group(P＜0.05);the constituent ratio of diarrhoeaand cholelithiasis was significantly lower in patients aged 18-64 years old group than patients aged≥65 years old group(P＜0.05).The constituent ratio of diarrhoea,vomiting,pancreatitis,cholecystitis,cholelithiasis,diabetic retinopathy,and acute kidney injurywas significantly higher in male group patients than in female group(P＜0.05).Conclusion Nausea,diarrhoea and vomiting remined the most common adverse events of semaglutide.Male should be more concerned about gastrointestinal,pancreatitis,gallbladder events,retinopathy and acute kidney injury.Elderly patients should be more alert diarrhoea and cholelithiasis.

Objective To investigate the incidence rate,clinical characteristics,and prognosis of neonatal stroke in Shenzhen,China.Methods Led by Shenzhen Children's Hospital,the Shenzhen Neonatal Data Collaboration Network organized 21 institutions to collect 36 cases of neonatal stroke from January 2020 to December 2022.The incidence,clinical characteristics,treatment,and prognosis of neonatal stroke in Shenzhen were analyzed.Results The incidence rate of neonatal stroke in 21 hospitals from 2020 to 2022 was 1/15 137,1/6 060,and 1/7 704,respectively.Ischemic stroke accounted for 75％(27/36);boys accounted for 64％(23/36).Among the 36 neonates,31(86％)had disease onset within 3 days after birth,and 19(53％)had convulsion as the initial presentation.Cerebral MRI showed that 22 neonates(61％)had left cerebral infarction and 13(36％)had basal ganglia infarction.Magnetic resonance angiography was performed for 12 neonates,among whom 9(75％)had involvement of the middle cerebral artery.Electroencephalography was performed for 29 neonates,with sharp waves in 21 neonates(72％)and seizures in 10 neonates(34％).Symptomatic/supportive treatment varied across different hospitals.Neonatal Behavioral Neurological Assessment was performed for 12 neonates(33％,12/36),with a mean score of(32±4)points.The prognosis of 27 neonates was followed up to around 12 months of age,with 44％(12/27)of the neonates having a good prognosis.Conclusions Ischemic stroke is the main type of neonatal stroke,often with convulsions as the initial presentation,involvement of the middle cerebral artery,sharp waves on electroencephalography,and a relatively low neurodevelopment score.Symptomatic/supportive treatment is the main treatment method,and some neonates tend to have a poor prognosis.

Objective:To evaluate the clinical and prognostic value of prothrombin time(PT)and activated partial thromboplastin time(APTT)in newly diagnosed patients with multiple myeloma(MM).Methods:The clinical data of 116 newly diagnosed MM patients in the Second Hospital and Third Hospital of Shanxi Medical University from October 2014 to March 2022 were analyzed retrospectively,and the patients were divided into two groups:normal PT and APTT group and prolonged PT or APTT group.The differences in sex,age,classification,staging,bleeding events,laboratory indicators[including hemoglobin(Hb),platelet count(PLT),serum calcium,serum albumin(ALB),lactate dehydrogenase(LDH),serum creatinine and β 2-microglobulin],and cytogenetic characteristics between the two groups of patients were compared.The effect of prolonged PT or APTT on survival of patients with MM was analyzed.Results:Compared with patients in normal PT and APTT group,patients in prolonged PT or APTT group were more likely to experience bleeding events(x2=5.087,P=0.024),with lower ALB levels(x2=4.962,P=0.026)and PLT levels(x2=4.309,P=0.038),and higher serum calcium levels(x2=5.056,P=0.025).The positive rates of del17p,del13q and 1q21+in prolonged PT or APTT group were higher than those in normal PT and APTT group,but the difference was not statistically significant(P＞0.05).K-M survival analysis showed that the prolonged PT or APTT group had a shorter median progression-free survival(PFS)(P=0.032)and overall survival(OS)(P=0.032).Multivariate Cox analysis showed that prolonged PT or APTT(HR=2.1 16,95％CI:1.025-4.372,P=0.043)and age ≥65 years(HR=2.403,95％CI:1.195-4.836,P=0.014)were independent risk factor for OS in newly diagnosed MM patients.However,prolonged PT or APTT had no significant effect on PFS of newly diagnosed MM patients(HR=1.162,95％CI:0.666-2.026,P=0.597).Conclusion:Newly diagnosed MM patients with prolonged PT or APTT have worse clinical indicators,shorter PFS and OS.Prolonged PT or APTT is an independent risk factor for OS in MM patients.

Objective:To assess the capability of seven reference medical laboratories to detect BCR::ABL1 p210 transcription levels and to compare the results among those laboratories.Methods:The interlaboratory comparison was carried out in two stages. The samples were prepared by the reference laboratory. The quantitative values of BCR::ABL1 p210 of the comparison samples covered 0.001%-0.01%, 0.01%-0.1%, 0.1%-1%, 1%-10% and>10% in each stage. Real-time quantitative PCR (RT-PCR) and dPCR (digital PCR) were used to examine the samples. The conversion factor (CF) was calculated and validated for each laboratory.Results:In the RT-PCR comparison, one laboratory was failed to detect BCR::ABL1 p210 in fourteen samples at the first stage. The results of the other six laboratories were qualified with the bias <±1.2 folds (-0.133-0.338) and 95% limits of agreement within ±5 folds (upper limit 0.147-0.785, lower limit -0.770--0.109), and the corresponding CF values were calculated and validated. In the dPCR comparison, one laboratory did not report results at the second stage. The results of the other six laboratories were qualified with the bias <±1.2 folds (-0.026-0.267) and 95% limits of agreement within±5 folds (upper limit 0.084-0.991, lower limit -0.669--0.135), and the corresponding CF values were calculated and validated. The samples with BCR::ABL1 p210 quantitative values of 0.01%-0.1%, 0.1%-1%, 1%-10% and >10% could be detected by both RT-PCR and qPCR. When the quantitative value of BCR::ABL1 p210 was 0.001%-0.01%, the detection rate of dPCR was higher than that of RT-PCR (85.56% vs. 68.00%).Conclusions:A good consistency is present among various laboratories. The quantitative value of BCR::ABL1 p210 is comparable among laboratories as shown by the CF value conversion. For quantitative detection of BCR::ABL1 p210 deep molecular reaction, dPCR has a higher positive detection rate and more advantages than RT-PCR. To ensure the accuracy and reproducibility of the BCR::ABL1 p210 test, it is imperative for every laboratory to enhance their daily quality control practices.

Objective: This study aims to overcome challenges in lumbar spine imaging, particularly lumbar spinal stenosis, by developing an automated segmentation model using advanced techniques. Traditional manual measurement and lesion detection methods are limited by subjectivity and inefficiency. The objective is to create an accurate and automated segmentation model that identifies anatomical structures in lumbar spine magnetic resonance imaging scans. Methods: Leveraging a dataset of 539 lumbar spinal stenosis patients, the study utilizes the residual U-Net for semantic segmentation in sagittal and axial lumbar spine magnetic resonance images. The model, trained to recognize specific tissue categories, employs a geometry algorithm for anatomical structure quantification. Validation metrics, like Intersection over Union (IOU) and Dice coefficients, validate the residual U-Net’s segmentation accuracy. A novel rotation matrix approach is introduced for detecting bulging discs, assessing dural sac compression, and measuring yellow ligament thickness. Results: The residual U-Net achieves high precision in segmenting lumbar spine structures, with mean IOU values ranging from 0.82 to 0.93 across various tissue categories and views. The automated quantification system provides measurements for intervertebral disc dimensions, dural sac diameter, yellow ligament thickness, and disc hydration. Consistency between training and testing datasets assures the robustness of automated measurements. Conclusion Automated lumbar spine segmentation with residual U-Net and deep learning exhibits high precision in identifying anatomical structures, facilitating efficient quantification in lumbar spinal stenosis cases. The introduction of a rotation matrix enhances lesion detection, promising improved diagnostic accuracy, and supporting treatment decisions for lumbar spinal stenosis patients.

Objective: This study aims to overcome challenges in lumbar spine imaging, particularly lumbar spinal stenosis, by developing an automated segmentation model using advanced techniques. Traditional manual measurement and lesion detection methods are limited by subjectivity and inefficiency. The objective is to create an accurate and automated segmentation model that identifies anatomical structures in lumbar spine magnetic resonance imaging scans. Methods: Leveraging a dataset of 539 lumbar spinal stenosis patients, the study utilizes the residual U-Net for semantic segmentation in sagittal and axial lumbar spine magnetic resonance images. The model, trained to recognize specific tissue categories, employs a geometry algorithm for anatomical structure quantification. Validation metrics, like Intersection over Union (IOU) and Dice coefficients, validate the residual U-Net’s segmentation accuracy. A novel rotation matrix approach is introduced for detecting bulging discs, assessing dural sac compression, and measuring yellow ligament thickness. Results: The residual U-Net achieves high precision in segmenting lumbar spine structures, with mean IOU values ranging from 0.82 to 0.93 across various tissue categories and views. The automated quantification system provides measurements for intervertebral disc dimensions, dural sac diameter, yellow ligament thickness, and disc hydration. Consistency between training and testing datasets assures the robustness of automated measurements. Conclusion Automated lumbar spine segmentation with residual U-Net and deep learning exhibits high precision in identifying anatomical structures, facilitating efficient quantification in lumbar spinal stenosis cases. The introduction of a rotation matrix enhances lesion detection, promising improved diagnostic accuracy, and supporting treatment decisions for lumbar spinal stenosis patients.

Objective: This study aims to overcome challenges in lumbar spine imaging, particularly lumbar spinal stenosis, by developing an automated segmentation model using advanced techniques. Traditional manual measurement and lesion detection methods are limited by subjectivity and inefficiency. The objective is to create an accurate and automated segmentation model that identifies anatomical structures in lumbar spine magnetic resonance imaging scans. Methods: Leveraging a dataset of 539 lumbar spinal stenosis patients, the study utilizes the residual U-Net for semantic segmentation in sagittal and axial lumbar spine magnetic resonance images. The model, trained to recognize specific tissue categories, employs a geometry algorithm for anatomical structure quantification. Validation metrics, like Intersection over Union (IOU) and Dice coefficients, validate the residual U-Net’s segmentation accuracy. A novel rotation matrix approach is introduced for detecting bulging discs, assessing dural sac compression, and measuring yellow ligament thickness. Results: The residual U-Net achieves high precision in segmenting lumbar spine structures, with mean IOU values ranging from 0.82 to 0.93 across various tissue categories and views. The automated quantification system provides measurements for intervertebral disc dimensions, dural sac diameter, yellow ligament thickness, and disc hydration. Consistency between training and testing datasets assures the robustness of automated measurements. Conclusion Automated lumbar spine segmentation with residual U-Net and deep learning exhibits high precision in identifying anatomical structures, facilitating efficient quantification in lumbar spinal stenosis cases. The introduction of a rotation matrix enhances lesion detection, promising improved diagnostic accuracy, and supporting treatment decisions for lumbar spinal stenosis patients.