To achieve rapid and visual detection of Plasmodium vivax,a detection method based on recombinase polymerase amplification(RPA)technology and lateral flow dipstick(LFD)was established and evaluated.Targeting the conserved sequence of the P.vivax 18S rRNA gene(GenBank:DQ660817.1)as the target sequence,primers and probes were designed with Primer Premier 5,and the P.vivax recombinant plasmid(pUCPv)was constructed as the standard.A sensitive and specific RPA-LFD-based rapid visual detection method for P.vivax nucleic acids was established.The plasmid standard was serially diluted 10-fold to concentrations of 1×103,1×102,1×101,1×10?,and 1×10?1 copies/μL for sensitivity testing.To evaluate specificity,whole blood DNA samples from patients infected with Plasmodium falciparum,Plasmodium malariae,Plasmodium ovale,or Leishmania donovani,as well as healthy participants,were tested by RPA-LFD.Additionally,The assay′s accuracy was evaluated by testing whole blood DNA samples from 24 confirmed P.vivax-infected patients.This study successfully established a sensitive,specific,and rapid visual RPA-LFD method for detecting P.vivax nucleic acids.The assay can complete P.vivax detection within 20 minutes under isothermal conditions at 39 ℃,achieving a sensitivity of 1 copy/μL.There is no significant cross reaction with parasites such as other Plasmodium species and L.donovani,and the specificity is 100%.All 24 DNA samples from confirmed P.vivax patients were detected,showing a 100%detection rate.The developed RPA-LFD assay exhibits excellent sensitivity and specificity,requires only simple heating equipment,and is user-friendly.This rapid visual detection method is particularly suitable for P.vivax screening in low-resource settings.

This article reports on the nursing experience in the rehabilitation of laryngeal function with primary tracheoesophageal puncture for voice prosthesis rehabilitation after laryngectomy.The core elements of postoperative nursing included:the use of a Heat and Moisture Exchanger(HME)for airway humidification to maintain pulmonary health;the implementation of progressive speech training to aid in the reconstruction of speech function;continuous monitoring and dilatation training to ensure the appropriate size of the stoma,thereby ensuring smooth breathing and speech;nasal airflow-inducing training for the promotion of olfactory rehabilitation;standardized maintenance of the voice prosthesis to extend its lifespan and reduce the occurrence of complications.After meticulous postoperative care,the patient showed good recovery of speech,olfaction,and respiratory function at the one-month follow-up,with the stoma diameter maintained at an ideal size and no complications occurred.

Vertical root fracture (VRF) often occurs in endodontically treated teeth. Root canal therapy (RCT) requires removal of part of the dentin, which affects the microhardness and elastic modulus of dentine, induces dentin microcracks, and increases the risk of VRF. The early diagnosis of VRF is challenging and the prognosis is poor, due to the absence of specific clinical manifestations. This narrative review analyzes the incidence and related factors of VRF after RCT from the perspective of etiology, discusses the effect and mechanism of each step during RCT on the occurrence of VRF, and briefly summarizes the diagnosis, prevention and treatment strategies of VRF, so as to reduce the occurrence of VRF and improve the prognosis of endodontically treated teeth.

Objective:To investigate the indications for prenatal diagnosis using copy number variation-sequencing (CNV-seq) and the abnormalities detected by the method.Methods:This retrospective analysis involved 17 994 singleton pregnant women who underwent prenatal CNV-seq at the First Affiliated Hospital of Zhengzhou University from January 2019 to December 2022. These cases were divided into five groups based on the following indications for CNV-seq: abnormal fetal ultrasound findings, high-risk results indicated by non-invasive prenatal testing (NIPT) or Down's syndrome serological screening (Down's screening), adverse pregnancy history, and advanced maternal age. The proportions of cases with the indications for prenatal CNV-seq, the detection rates of abnormalities (numerical abnormalities of chromosomes, pathogenic/likely pathogenic CNV in structural abnormalities) in the five groups, and the distribution of these abnormalities were analyzed. Statistical analysis was performed using Chi-square test. Results:Among the 17 994 pregnant women, the women with abnormal fetal ultrasound findings, high-risk NIPT results, high-risk Down's screening results, adverse pregnancy history, and advanced maternal age accounted for 32.65% (5 875/17 994), 11.90% (2 142/17 994), 31.62% (5 690/17 994), 11.70% (2 105/17 994), and 12.13% (2 182/17 994), respectively. The detection rates of abnormalities in the five groups were 10.60% (623/5 875), 34.64% (742/2 142), 4.69% (267/5 690), 2.99% (63/2 105), and 3.67% (80/2 182), respectively. The overall detection rate of abnormalities was 9.86% (1 775/17 994). The cases with numerical abnormalities of chromosomes accounted for 68.79% (1 221/1 775), trisomy 21 was predominant (49.30%, 602/1 221). Chromosomal structural abnormalities were detected in 31.21% (554/1 775) of the cases with abnormalities, with 57.76% (320/554) harboring pathogenic CNVs and 42.24% (234/554) harboring likely pathogenic CNVs. The detection rate of chromosomal numerical abnormalities was higher than that of structural abnormalities in the abnormal fetal ultrasound group, NIPT high-risk group, and advanced maternal age group [6.81% (400/5 875) vs. 3.80% (223/5 875), χ2=53.10; 27.96% (599/2 142) vs. 6.68% (143/2 142), χ2=338.40; 2.43% (53/2 182) vs. 1.24% (27/2 182), χ2=8.61; all P<0.01]. A total of 416 microdeletions and 255 microduplications were detected in the 554 cases. The top three regions with the highest frequencies in microdeletions were Xp22.31 (12.74%, 53/416), 22q11.21 (7.93%, 33/416), and 17q12 (5.77%, 24/416); in microduplications, they were 22q11.21 (14.90%, 38/255), 17q12 (3.53%, 9/255), and 7q11.23 (3.53%, 9/255). Conclusions:Abnormal fetal ultrasound findings accounted for the highest proportion of prenatal diagnostic indications. The overall detection rate of abnormalities by CNV-seq is relatively high, especially in those with high-risk NIPT results as an indication for prenatal diagnosis. Among the chromosomal structural abnormalities detected in this study, the frequencies of Xp22.31 microdeletion and 22q11.21 microduplication are higher.

Objective:To construct a thyroid nodule segmentation model using ultrasound dynamic images and explore its potential for assisting in the screening of thyroid nodules.Methods:A total of 126 patients with thyroid nodules（comprising 150 nodules）who were diagnosed and treated at Xuzhou Cancer Hospital from April 2024 to December 2024 were prospectively enrolled. Two-dimensional ultrasound was performed to capture short-axis and long-axis video images of thyroid nodules，forming a dynamic ultrasound image dataset. The dataset was divided into training，validation，and test sets in a ratio of 6∶1∶3. After the training loss curve converged，the model that performed well on the validation set was selected for testing. Three-fold cross-validation was employed for training and testing. All 300 ultrasound videos were divided into three subsets. In each experiment，two subsets were used as the training set，and one subset was used as the test set to evaluate the model's generalization ability. A collaborative spatiotemporal diffusion model was established based on the dynamic trends and tissue texture details of thyroid nodules. Six widely used segmentation metrics were employed to evaluate the model's application capabilities.Results:The study included 126 patients with 150 thyroid nodules，300 dynamic ultrasound images，and video lengths of 3-4 seconds per nodule，resulting in 12 312 segmented images. The size of the thyroid nodules was（10.7 ± 10.6）mm（transverse diameter）×（8.4 ± 6.3）mm（anteroposterior diameter）. Among the nodules，62（41.3%）had clear boundaries，while 88（58.7%）had indistinct boundaries；61（40.7%）exhibited regular shapes，while 89（59.3%）were irregular；66（44.0%）had a taller-than-wide aspect ratio；and 70（46.7%）showed microcalcifications. The collaborative diffusion model based on dynamic ultrasound image segmentation achieved the following scores：a Jaccard score of（69.22 ± 0.03）%，a Dice score of（79.16 ± 0.18）%，a Precision score of（86.70 ± 0.17）%，a Recall score of（77.82 ± 0.04）%，an Sα score of（85.26 ± 0.01）%，and an Eθmn score of（90.58 ± 0.17）%. Compared to other models，this model demonstrated significant improvements across all evaluation metrics，achieving the highest values in each metric with increments of over 8% and 1%，respectively. Conclusions:The collaborative diffusion model with a dynamic controller，constructed based on dynamic ultrasound images of thyroid nodules，demonstrates excellent performance in ultrasound image segmentation. It improves the accuracy of thyroid nodule screening，thereby providing a valuable auxiliary diagnostic tool for clinical practice.

Objective:To propose a deep learning（DL）-based ultrasound imaging auxiliary tool for automatic segmentation and recognition of the brachial plexus（BP），and to enhance the accuracy and safety of clinical procedures.Methods:It was a multicenter study that collected 773 healthy subjects from Peking University Third Hospital and its branch campuses，the Third Medical Center of the Chinese PLA General Hospital，and Shanghai Eighth People's Hospital between August 2024 and February 2025. Brachial plexus（BP）images in the interscalene groove were captured used high-frequency ultrasound by senior sonographers，a dataset comprising 1 289 standardized images were constructed and the improved model（CHA-TransUNet）was trained. The test set was input into 6 different models（CHA-TransUNet，R50-Unet，TransUnet，SegFormer，SwinUnet，MISSFormer）for segmentation. Segmentation accuracy was evaluated using metrics including the Dice similarity coefficient（DSC），95% Hausdorff distance（HD95）and mean intersection over union（mIoU），and was compared with the segmentation results of 3 ultrasound physicians with varying experience levels（junior physicians and senior physicians）to validate the model's segmentation efficacy.Results:The CHA-TransUNet model established based on a dataset of 1 289 standardized images achieved segmentation results for the BP with a DSC of 90.15%，mIoU of 91.02%，and HD95 of 8.08. Its accuracy was higher than other mainstream models（DSC：90.15% vs. 87.60%，87.77%，81.35%，84.78%，84.55%），significantly better than junior physicians（DSC：90.15% vs. 68.73%， Z=-127.76， P<0.001），and approached the level of senior physician（DSC：90.15% vs. 86.15%， Z=-31.33， P=0.549）. The model demonstrated superior boundary recognition in complex anatomical structures（e.g.，C6/C7 nerve roots）compared to ultrasound physicians（junior and senior）（HD95：8.08 vs. 26.34，17.44，56.80）. Conclusions:This study proposes an analysis model for BP ultrasound images，CHA-TransUNet. This model achieves segmentation and recognition of the BP with relatively complex pathways and structures. The model exhibits high accuracy and stability，outperforming current mainstream network models and junior physicians while approaching the performance level of senior physicians. It assists junior physicians or trainees in more accurately identifying and localizing the BP.

Objective:To investigate the indications for prenatal diagnosis using copy number variation-sequencing (CNV-seq) and the abnormalities detected by the method.Methods:This retrospective analysis involved 17 994 singleton pregnant women who underwent prenatal CNV-seq at the First Affiliated Hospital of Zhengzhou University from January 2019 to December 2022. These cases were divided into five groups based on the following indications for CNV-seq: abnormal fetal ultrasound findings, high-risk results indicated by non-invasive prenatal testing (NIPT) or Down's syndrome serological screening (Down's screening), adverse pregnancy history, and advanced maternal age. The proportions of cases with the indications for prenatal CNV-seq, the detection rates of abnormalities (numerical abnormalities of chromosomes, pathogenic/likely pathogenic CNV in structural abnormalities) in the five groups, and the distribution of these abnormalities were analyzed. Statistical analysis was performed using Chi-square test. Results:Among the 17 994 pregnant women, the women with abnormal fetal ultrasound findings, high-risk NIPT results, high-risk Down's screening results, adverse pregnancy history, and advanced maternal age accounted for 32.65% (5 875/17 994), 11.90% (2 142/17 994), 31.62% (5 690/17 994), 11.70% (2 105/17 994), and 12.13% (2 182/17 994), respectively. The detection rates of abnormalities in the five groups were 10.60% (623/5 875), 34.64% (742/2 142), 4.69% (267/5 690), 2.99% (63/2 105), and 3.67% (80/2 182), respectively. The overall detection rate of abnormalities was 9.86% (1 775/17 994). The cases with numerical abnormalities of chromosomes accounted for 68.79% (1 221/1 775), trisomy 21 was predominant (49.30%, 602/1 221). Chromosomal structural abnormalities were detected in 31.21% (554/1 775) of the cases with abnormalities, with 57.76% (320/554) harboring pathogenic CNVs and 42.24% (234/554) harboring likely pathogenic CNVs. The detection rate of chromosomal numerical abnormalities was higher than that of structural abnormalities in the abnormal fetal ultrasound group, NIPT high-risk group, and advanced maternal age group [6.81% (400/5 875) vs. 3.80% (223/5 875), χ2=53.10; 27.96% (599/2 142) vs. 6.68% (143/2 142), χ2=338.40; 2.43% (53/2 182) vs. 1.24% (27/2 182), χ2=8.61; all P<0.01]. A total of 416 microdeletions and 255 microduplications were detected in the 554 cases. The top three regions with the highest frequencies in microdeletions were Xp22.31 (12.74%, 53/416), 22q11.21 (7.93%, 33/416), and 17q12 (5.77%, 24/416); in microduplications, they were 22q11.21 (14.90%, 38/255), 17q12 (3.53%, 9/255), and 7q11.23 (3.53%, 9/255). Conclusions:Abnormal fetal ultrasound findings accounted for the highest proportion of prenatal diagnostic indications. The overall detection rate of abnormalities by CNV-seq is relatively high, especially in those with high-risk NIPT results as an indication for prenatal diagnosis. Among the chromosomal structural abnormalities detected in this study, the frequencies of Xp22.31 microdeletion and 22q11.21 microduplication are higher.

To achieve rapid and visual detection of Plasmodium vivax,a detection method based on recombinase polymerase amplification(RPA)technology and lateral flow dipstick(LFD)was established and evaluated.Targeting the conserved sequence of the P.vivax 18S rRNA gene(GenBank:DQ660817.1)as the target sequence,primers and probes were designed with Primer Premier 5,and the P.vivax recombinant plasmid(pUCPv)was constructed as the standard.A sensitive and specific RPA-LFD-based rapid visual detection method for P.vivax nucleic acids was established.The plasmid standard was serially diluted 10-fold to concentrations of 1×103,1×102,1×101,1×10?,and 1×10?1 copies/μL for sensitivity testing.To evaluate specificity,whole blood DNA samples from patients infected with Plasmodium falciparum,Plasmodium malariae,Plasmodium ovale,or Leishmania donovani,as well as healthy participants,were tested by RPA-LFD.Additionally,The assay′s accuracy was evaluated by testing whole blood DNA samples from 24 confirmed P.vivax-infected patients.This study successfully established a sensitive,specific,and rapid visual RPA-LFD method for detecting P.vivax nucleic acids.The assay can complete P.vivax detection within 20 minutes under isothermal conditions at 39 ℃,achieving a sensitivity of 1 copy/μL.There is no significant cross reaction with parasites such as other Plasmodium species and L.donovani,and the specificity is 100%.All 24 DNA samples from confirmed P.vivax patients were detected,showing a 100%detection rate.The developed RPA-LFD assay exhibits excellent sensitivity and specificity,requires only simple heating equipment,and is user-friendly.This rapid visual detection method is particularly suitable for P.vivax screening in low-resource settings.

This article reports on the nursing experience in the rehabilitation of laryngeal function with primary tracheoesophageal puncture for voice prosthesis rehabilitation after laryngectomy.The core elements of postoperative nursing included:the use of a Heat and Moisture Exchanger(HME)for airway humidification to maintain pulmonary health;the implementation of progressive speech training to aid in the reconstruction of speech function;continuous monitoring and dilatation training to ensure the appropriate size of the stoma,thereby ensuring smooth breathing and speech;nasal airflow-inducing training for the promotion of olfactory rehabilitation;standardized maintenance of the voice prosthesis to extend its lifespan and reduce the occurrence of complications.After meticulous postoperative care,the patient showed good recovery of speech,olfaction,and respiratory function at the one-month follow-up,with the stoma diameter maintained at an ideal size and no complications occurred.

Objective:To construct a thyroid nodule segmentation model using ultrasound dynamic images and explore its potential for assisting in the screening of thyroid nodules.Methods:A total of 126 patients with thyroid nodules（comprising 150 nodules）who were diagnosed and treated at Xuzhou Cancer Hospital from April 2024 to December 2024 were prospectively enrolled. Two-dimensional ultrasound was performed to capture short-axis and long-axis video images of thyroid nodules，forming a dynamic ultrasound image dataset. The dataset was divided into training，validation，and test sets in a ratio of 6∶1∶3. After the training loss curve converged，the model that performed well on the validation set was selected for testing. Three-fold cross-validation was employed for training and testing. All 300 ultrasound videos were divided into three subsets. In each experiment，two subsets were used as the training set，and one subset was used as the test set to evaluate the model's generalization ability. A collaborative spatiotemporal diffusion model was established based on the dynamic trends and tissue texture details of thyroid nodules. Six widely used segmentation metrics were employed to evaluate the model's application capabilities.Results:The study included 126 patients with 150 thyroid nodules，300 dynamic ultrasound images，and video lengths of 3-4 seconds per nodule，resulting in 12 312 segmented images. The size of the thyroid nodules was（10.7 ± 10.6）mm（transverse diameter）×（8.4 ± 6.3）mm（anteroposterior diameter）. Among the nodules，62（41.3%）had clear boundaries，while 88（58.7%）had indistinct boundaries；61（40.7%）exhibited regular shapes，while 89（59.3%）were irregular；66（44.0%）had a taller-than-wide aspect ratio；and 70（46.7%）showed microcalcifications. The collaborative diffusion model based on dynamic ultrasound image segmentation achieved the following scores：a Jaccard score of（69.22 ± 0.03）%，a Dice score of（79.16 ± 0.18）%，a Precision score of（86.70 ± 0.17）%，a Recall score of（77.82 ± 0.04）%，an Sα score of（85.26 ± 0.01）%，and an Eθmn score of（90.58 ± 0.17）%. Compared to other models，this model demonstrated significant improvements across all evaluation metrics，achieving the highest values in each metric with increments of over 8% and 1%，respectively. Conclusions:The collaborative diffusion model with a dynamic controller，constructed based on dynamic ultrasound images of thyroid nodules，demonstrates excellent performance in ultrasound image segmentation. It improves the accuracy of thyroid nodule screening，thereby providing a valuable auxiliary diagnostic tool for clinical practice.