ObjectiveHistorically documented Zhejiang Atractylodis Macrocephalae Rhizoma（Baizhu） possesses premium characteristics such as phoenix-like head and crane-like neck， pronounced sweetness， and fragrant aroma. However， its current market circulation is low， and the processed products with Zhejiang-style characteristics are at the risk of being lost. This study aims to preserve the ancient Zhejiang-style processing techniques and evaluate them using modern scientific methods. MethodsMultidimensional intelligent sensory evaluation was used to digitally characterize the "quality-structure" of the external appearance of nine-steamed and nine-processed Baizhu medicinal materials（intermediate processed products） and the "odor-taste" of the internal quality of its decoction pieces（slices）， and the appearance parameters were digitally characterized by colorimeter， texture analyzer， electronic nose and electronic tongue， the chemical composition was analyzed via ultra-performance liquid chromatography-quadrupole-time-of-flight mass spectrometry（UPLC-Q-TOF-MS/MS）. Then， cluster analysis on the differences in odor between the medicinal materials（intermediate processed products） and decoction pieces（slices） of nine-steamed and nine-processed Baizhu was conducted， as well as the differences in taste between water-soluble and alcohol-soluble extracts of the decoction pieces（slices）， and the correlation analysis of chroma value-alcohol-soluble extract content-component response value. ResultsThe nine-steamed and nine-processed Baizhu had a dark brown to black epidermis， a brownish-yellow to brownish-gray cross-section， a slightly tough texture， a faint odor， and a slightly sweet， bitter and pungent taste. Texture analyzer measurements revealed minimal adhesion and maximum recovery in the middle section of the characteristic processed Baizhu， consistent with the processing endpoint of thorough steaming and cooking. The head section showed the highest internal hardness， elasticity and chewiness， indicating a denser texture in this area. The electronic nose sensor could clearly distinguish the difference between the medicinal materials and its decoction pieces， with a more significant clustering effect at 60 ℃ for 30 minutes compared to ambient temperature headspace for 2 hours， highlighting the significant impact of the baking degree before slicing on the quality. The electronic tongue taste signal map clearly distinguished the differences between water-soluble and alcohol-soluble extracts of nine-steamed and nine-processed Baizhu decoction pieces， and the addition of auxiliary materials during processing could enhance its alcohol-soluble extract content. A total of 82 chemical components were identified in the characteristic processed Baizhu. After processing， the contents of 58 components increased， while 24 components decreased. Correlation analysis revealed significant negative correlations（P<0.01） between ethanol-soluble extract content and colorimetric values of brightness（L^*）， yellow-bule value（b^*）， and total color difference（E^*_ab）. E^*_ab showed marked negative correlations（P<0.05） with the response values of isochlorogenic acid A and C. ConclusionThis study establishes a modern intelligent sensory evaluation model for multidimensional holographic characterization of nine-steamed and nine-processed Baizhu， clarifying the correlation between increased isochlorogenic acid content and the visual color appearance after different steaming cycles， as well as its intrinsic alcohol-soluble extracts. This provides a reference for quality evaluation and processing standards of the Zhejiang-style characteristic processed products.

With the continuous deepening of the concept of precision diagnosis and treatment for lung cancer, how to achieve higher efficiency and accuracy in the screening, diagnosis, and treatment pathways in clinical practice has become an important issue that urgently needs to be overcome. The current clinical difficulty lies in the fact that despite continuous advancements in imaging and molecular diagnostic technologies, there are still limitations in manual efficiency and subjective experience when it comes to massive data analysis and multi-scale feature extraction. Artificial intelligence (AI), especially algorithm systems based on deep learning, is an innovative technology capable of deeply empowering medical big data. This method utilizes algorithms such as convolutional neural networks, combined with radiomics, pathomics, and multi-modal data fusion analysis, demonstrating immense potential in early precise detection and benign-malignant differentiation of pulmonary nodules, digital pathological subtype recognition and non-invasive prediction of driver genes, precise 3D surgical planning and automatic delineation of radiotherapy target volumes, as well as dynamic risk warning during follow-up. This innovative technology provides a brand-new solution for realizing intelligent and individualized lung cancer diagnosis and treatment models. This consensus, based on the latest evidence from evidence-based medicine and combined with the development trends in the AI field and real-world clinical needs, was ultimately formed by gathering the consensus opinions of multidisciplinary experts in radiology, pathology, thoracic surgery, and other fields. The main content covers the application specifications of AI in the three core scenarios of lung cancer screening, diagnosis, and treatment, the technical standards for data collection and algorithm validation, as well as the ethical and regulatory challenges faced at the current stage. It aims to clarify the applicable boundaries of AI as a clinical auxiliary decision support tool, providing scientific guidance and standardized exploration directions for peers currently engaged in or planning to carry out AI-assisted clinical diagnosis, treatment, and translation of lung cancer.

Objective This study reports on the obligatory parasitism of water mites Arrenurus sp. on Anopheles messeae at the Manzhouli Port, Inner Mongolia, China. Methods Duing July 2024, a survey on the mosquito diversity was conducted at the Manzhouli Port. Captured mosquitoes and their ectoparasites were identified to species level. Results A total of 1840 adult mosquitoes were collected, representing species from three genera: Culex(Cx. modestus, Cx. pipiens pallens), Aedes(Ae. dorsalis, Ae. flavidorsalis, Ae. flavescens), and Anopheles (An. messeae). Among all the mosqutioes specimens,3 out of 150 captured An. messeae were found to carry ectoparasitic mites, with number of 2,4,27 mites separately. Morphological and molecular identification reached the same result as water mites(Hydrachnidiae, Hydracrina). COI gene sequence showed 94% similarity with the closest species Arrenurus truncatellus. Conlusions Literature review suggests water mites are host-specific parasitism of mosquito species and herein with the first record of Arrenurus sp. parasiting on An. Messeae in the most high-latitude region globally.

With the widespread adoption of low-dose CT screening and the extensive application of high-resolution CT, the detection rate of sub-centimeter lung nodules has significantly increased. How to scientifically manage these nodules while avoiding overtreatment and diagnostic delays has become an important clinical issue. Among them, lung nodules with a consolidation tumor ratio less than 0.25, dominated by ground-glass shadows, are particularly worthy of attention. The therapeutic challenge for this group is how to achieve precise and complete resection of nodules during surgery while maximizing the preservation of the patient's lung function. The "watershed topography map" is a new technology based on big data and artificial intelligence algorithms. This method uses Dicom data from conventional dose CT scans, combined with microscopic (22-24 levels) capillary network anatomical watershed features, to generate high-precision simulated natural segmentation planes of lung sub-segments through specific textures and forms. This technology forms fluorescent watershed boundaries on the lung surface, which highly fit the actual lung anatomical structure. By analyzing the adjacent relationship between the nodule and the watershed boundary, real-time, visually accurate positioning of the nodule can be achieved. This innovative technology provides a new solution for the intraoperative positioning and resection of lung nodules. This consensus was led by four major domestic societies, jointly with expert teams in related fields, oriented to clinical practical needs, referring to domestic and foreign guidelines and consensus, and finally formed after multiple rounds of consultation, discussion, and voting. The main content covers the theoretical basis of the "watershed topography map" technology, indications, operation procedures, surgical planning details, and postoperative evaluation standards, aiming to provide scientific guidance and exploration directions for clinical peers who are currently or plan to carry out lung nodule resection using the fluorescent microscope watershed analysis method.

Objective To investigate the clinical characteristics of colorectal polyps in patients with melanosis coli(MC),analyze the recurrence risk after polypectomy,and construct a prediction model for polyp recurrence.Methods A total of 1,763 patients who underwent colorectal polypec-tomy at the First Hospital of Handan from January 2017 to June 2023 were divided into MC group(n=149)and non-MC group(n=1,614).Among them,122 patients in the MC group underwent colonoscopic re-examination one year later and were further divided into recurrence group(n=52)and non-recurrence group(n=70)based on polyp recurrence.The characteristics of colorectal polyps and recurrence risk after polypectomy in MC patients were analyzed.A multivariable Logistic regression analysis was used to construct a polyp recurrence risk model,and the nomogram model was plotted using R studio software.The receiver operating characteristic(ROC)curve,calibration curve,and decision curve analysis were employed to evaluate the discrimination,calibration,and clinical practicality of the model.Results The detection rates of large polyps(≥1.0 cm),right-sided colon polyps,multiple polyps(≥3 polyps),and Yamada type Ⅰ polyps in the MC group were significantly higher than those in the non-MC group,while the detection rates of left-sided co-lon polyps and Yamada type Ⅳ polyps were significantly lower(P＜0.05).The detection rates of adenomatous polyps and polyps with mild dysplasia in the MC group were significantly higher than those in the non-MC group,whereas the detection rate of polyps with moderate dysplasia in the MC group was significantly lower(P＜0.05).Significant differences were observed between the recur-rence and non-recurrence groups in terms of a history of cholecystectomy,Helicobacter pylori(Hp)in-fection,and family history of colorectal cancer(P＜0.05).There were also significant differences in the distribution,size,and the number of initial polyps between the two groups(P＜0.05).Multivari-able Logistic regression analysis identified cholecystectomy,Hp infection,first-degree relatives with colorectal cancer,polyp size(≥1 cm),and multiple polyps(≥3 polyps)as independent risk factors for polyp recurrence after polypectomy(P＜0.05).Based on these factors,a recurrence prediction model was constructed.The area under the curve(AUC)of this model was 0.824(95％CI,0.753 to 0.895),indicating good discrimination.The calibration curve showed a good fit.Decision curve anal-ysis demonstrated a high net benefit within the threshold range of 0.1 to 0.8,suggesting that the mod-el had a wide range of beneficial thresholds and clinical practical value.Conclusion Compared with the non-MC group,the MC group has higher detection rates of large polyps,right-sided colon pol-yps,multiple polyps,Yamada type Ⅰ polyps,adenomatous polyps,and polyps with low-grade dys-plasia,but lower detection rates of left-sided colon polyps,Yamada type Ⅳ polyps,and polyps with moderate dysplasia.Cholecystectomy,Hp infection,first-degree relatives with colorectal cancer,large polyps(≥1 cm),and multiple polyps(≥3 polyps)are independent risk factors for polyp re-currence after colorectal polypectomy in MC patients.The recurrence prediction model constructed based on these factors has high practical value.

Objective To construct a mammography image classification assistant system suitable for Chinese population,and explore the potential of artificial intelligence technology to assist early screening of breast cancer in China.Methods Curated breast imaging subset of digital database for screening mammography(CBIS-DDSM),Mammographic image analysis society database(MIAS)and other international open datasets were used to conduct model training respectively in order to reproduce the mainstream in-depth learning methods in the current literature.The model was also tested on the Chinese breast mammography database(CBMD)provided by Huajiao Technology Co.,Ltd,and the performance was compared.Aiming at the problem that the Chinese population data are not ideal in the performance test of the open dataset training model,an optimization strategy based on the sliding window adjustment mechanism was implemented in combination with the characteristics of Chinese population data.Then a two-stage migration learning method was designed to improve the overall performance of the model,and then development of our system was carried out.Results With the sliding window adjustment mechanism and the CBMD training model after two-stage transfer learning,the accuracy of our developed system was improved from 0.50 of the open datasets to 0.80,precision from 0.54 to 0.82,sensitivity from 0.52 to 0.80,F1 value from 0.52 to 0.80,and AUC value from 0.51 to 0.89 based on the Chinese population dataset as the test set.Conclusion Through the introduction of sliding window adjustment mechanism and two-stage migration learning strategy,the performance of the breast molybdenum target image classification model has been significantly improved in the Chinese population dataset,and our system primarily achieves the purpose of assisting the classification of breast molybdenum target images for the Chinese population.

Objective To identify risk factors for colorectal adenomatous polyps using logistic regression analysis,construct a prediction model based on these identified factors,and subsequently evaluate the performance of the model.Methods Encompassed 1,023 patients who underwent large intestine polyp resection at the First Hospital of Handan between January 2017 and January 2022.Among these patients,676 had adenomatous polyps(adenomatous polyp group)and 347 had non-adenomatous polyps(non-adenomatous polyp group).We collected data on basic information,medical history,colonoscopy results,and polyp pathology.By comparing the two groups,we identified significant differences in various indicators,which were selected as candidate factors for model construction.Patients were randomly divided into a training set and a validation set at an 8∶2 ratio.Using the training set data,we constructed a risk prediction model and developed a nomogram using R Studio software to visually present the model.Finally,we internally validated the model using the validation set.The model's discrimination ability was evaluated using the ROC curve,its accuracy was assessed via the calibration curve,and its clinical utility was evaluated through decision curve analysis(DCA).Results Significant differences were observed between the two groups in terms of age,drinking habits,family history of colorectal cancer,hyperlipid-emia,history of cholecystectomy,HP infection,and history of appendectomy(P<0.05).These variables were included in the model construction.A total of 818 participants were randomly assigned to the training set,while 205 were allocated to the validation set.Multivariate logistic regression analysis on the training set confirmed that age(OR=1.021,95%CI:1.006～1.036,P=0.006),alcohol consumption(OR=3.440,95%CI:2.251～5.257,P<0.001),first-degree relatives with colorectal cancer(OR=3.775,95%CI:1.881～7.577,P<0.001),hyperlipidemia(OR=3.428,95%CI:2.443～4.808,P<0.001),history of cholecystectomy(OR=3.916,95%CI:1.756～8.735,P<0.001),Helicobacter pylori(HP)infection(OR=3.292,95%CI:2.309～4.693,P<0.001),and history of appendectomy(OR=3.819,95%CI:2.002～7.286,P<0.001)were independent risk factors for adenomatous polyps.Consequently,a prediction model for large intestine adenomatous polyps was developed using the formula P=1/(1+e-Y),where Y=0.020×age+1.328×first-degree relatives with colorectal cancer+1.235×alcohol consumption+1.232×hyperlipidemia+1.365×cholecystectomy+1.192×HP infection+1.340×appendectomy-1.995.The model demonstrated good performance with AUC values of 0.763(95%CI:0.729～0.797)for the training set and 0.769(95%CI:0.644～0.787)for the validation set.The calibration curve indicated a good fit,and decision curve analysis showed that the model could achieve positive net benefit across a wide range of threshold probabilities,confirming its clinical utility.Conclusions Age,alcohol consumption,a family history of colorectal cancer in first-degree relatives,hyperlipidemia,cholecystectomy,HP infection,and appendectomy were identified as independent risk factors for adenomatous polyps.A prediction model incorporating these risk factors holds significant practical value for predicting the occurrence of colorectal adenomatous polyps.

Objective To explore the challenges faced by online appointment nurses during nasogastric intubation and to provide a reference for improvement of the quality and safety of the services provided by online appointment nursing.Methods A purposive sampling was employed to select 13 online appointment nurses from our hospital who had previously provided home nasogastric intubation services for patients.Semi-structured interviews were conducted with the online appointment nurses.The results acquired from the interviews were analysed using Colaizzi's method.Results Two themes were identified.Theme 1 covered the increased risks of nasogastric intubation due to the patients themselves and home environment,which included 4 sub-themes of difficulties in identification and response due to complex conditions of patient,high risk of a sudden asphyxia with poor resuscitation facility,psychological stress from unfamiliar home environment,and more challenges in risk identification due to limited conditions for performing home-based intubation procedures;Theme 2 covered the coping strategies of online-scheduled nurses,which included the improvement of knowledge and skills in emergency nursing to improve comfidence and judge ability of intubation,the strengthening of nurse-patient communication to build a trust and cooperation,the conduct of thorough assessment to ensure procedural safety,and the use of alternative tools and collaboration with family members.Conclusion Online appointment nurses face challenges and risks from both of the procedures and patients themselves during home based nasogastric intubation.Hospitals and relevant management should actively implement corresponding strategies,provide training and guidance for online appointment nurses,develop relevant regulations,and improve the management mechanisms of the internet platform to ensure the safety of home based nasogastric intubation for online appointment nurses and improve the quality of the"Internet Plus Nursing Services."

Objective:To elucidate the genomic characteristics of the immunoglobulin (IG) heavy-chain variable region and light-chain variable region, the expression of subclones, and the prognostic significance in patients with CLL.Methods:Blood and/or bone marrow specimens were gathered from a cohort of 36 patients with CLL diagnosed at Jiangsu Province Hospital from December 2018 to May 2023, including 12 cases of B cell receptor (BCR) stereotyped patients. IG heavy-chain (IGH) and light-chain (IG Kappa [IGK] and IG lambda [IGL]) gene rearrangements were performed using next-generation sequencing (NGS) technology to analyze the characteristics and prognostic value in CLL.Results:NGS detection of IG variable region (IGHV) demonstrated a significant correlation and superior consistency with Sanger sequencing ( r=0.957, P < 0.001). Among the 36 patients, the IGH variant (IGHV) was observed in 9 (25.0%) but not in 27 (75.0%) participants. The incidence of the MYD88 mutation was higher among patients with mutated IGHV [1/27 (3.7%) vs 4/9 (44.4%), P=0.00]. A high incidence of trisomy 12 was observed in the IGHV #8/#8B subset [4/11 (36.4%) vs 1/25 (4.0%), P=0.023], which were more likely to develop Richter transformation [8/11 (72.7%) vs 4/25 (16.0%), P=0.002]. In the patient cohort, 36 individuals (36/36, 100.0%) used the IGK variable, whereas 15 individuals (15/36, 41.7%) employed the IGL variable (IGLV). IGLV3 - 21 reported the highest utilization rate in IGLV (5/15, 33.3%). Remarkably, patients with CLL with IGLV3-21 fragments were exclusively observed in the Binet C stage and Rai Phase Ⅲ-Ⅳ, with an incidence of del (13) (q14) at 60.0% (3/5). The median time to first treatment (TTFT) of patients with or without IGLV3 - 21 fragments was 5.2 (1.1 - 41.5) and 9.9 (0.1 - 94.4) months, respectively. Using the total reads threshold of 2.5%, 4 (4/36, 11.1%) samples were detected to have two IGHV productive clones. The median TTFT and overall survival (OS) time were 2.8 (0.9-72.7) and 12.8 months in patients with one mutated clone and 57.5 (32.0-120.7) and 51.8 months in those with two mutated clones, respectively. The median TTFT and OS time were 10.9 (0.3-94.4) and 6.3 (0.1 - 12.5) months in patients with one unmutated clone and 49.9 (22.2 - 211.1) and 30.0 (9.6 - 50.3) months in those with multiple unmutated clones, respectively ( P>0.05) . Conclusions:Detection of IG gene rearrangements using NGS technology not only facilitates the analysis of the IGHV mutation status, dominant clones, and prognostic value but also contributes to the exploration of IGK/IGL gene rearrangement fragments and the utilization of subclones. Further, it provides information about the poor prognosis of IGLV3 - 21 CLL. The shortened survival of the two unmutated clone groups in the IGHV unmutated group may indicate a poor prognosis.

Objective:To investigate the clinicopathological features, diagnosis, and prognosis of aggressive natural killer-cell leukemia (ANKL).Methods:A retrospective analysis was conducted on 27 ANKL patients treated at the First Affiliated Hospital of Nanjing Medical University from 2014 to 2024. Their clinical data, histomorphology, and immunophenotype were reviewed. Kaplan-Meier analysis was used to evaluate the overall survival (OS), and COX regression analysis was performed to identify prognostic factors affecting OS.Results:Among the 27 patients, 18 were male and 9 were female, with a male-to-female ratio of 2∶1. The age ranged from 15-75 years, with a median age of 42.0 (28.5, 54.5) years. Fever and splenomegaly were the most common signs and symptoms. Most patients presented with pancytopenia, coagulation abnormalities, and liver dysfunction; and all patients had elevated EBV loads. Microscopically, 16 cases showed marked to hypercellular bone marrow proliferation, with predominant interstitial infiltration (15 cases, 55.6%), followed by sinusoidal infiltration (3 cases), diffuse infiltration (6 cases, 22.2%), mixed infiltration (interstitial and focal, 3 cases, 11.1%), focal infiltration (2 cases, 7.4%), and nodular infiltration (1 case, 3.7%). The proportion of tumor cells among nucleated cells ranged from 2% to 80%, with a median of 30%. The tumor cells displayed variable morphology. Hemophagocytosis was observed in 23 cases. Immunohistochemistry revealed that all cases expressed CD56, with mostly expressing cytotoxic molecules (granzyme B, TIA-1). The Ki-67 proliferative index ranged from 50% to 90%. CD56-EBER dual staining showed that NK cells were the primary targets of the virus. Reticulin staining showed increased fibrosis. By flow cytometry, all cases were positive for CD2 but negative for surface CD3 (sCD3), CD4, CD5 and CD57. Among them, 21 cases (95.5%) exhibited a typical phenotype of strong CD56 expression (CD56str+) with CD16 negativity (CD16-), while only one case (4.5%) showed CD16 positivity (CD16+) with dim CD56 expression (CD56dim). In killer-cell immunoglobulin-like receptor (KIR) analysis, 6 out of 17 patients (6/17) demonstrated monoclonal expression, including CD158a (4/6), CD158i (1/6), and CD158e (1/6); the remaining 11 cases (11/17) showed complete absence of KIR expression. All tested cases (17/17) were negative for T-cell receptor (TCR) protein expression. Follow-up period was from 257 days, 1 patient was lost to follow-up, and the remaining 26 patients died. Kaplan-Meier analysis revealed that OS was significantly longer in patients who received chemotherapy compared to those who did not ( P<0.05). Univariate Cox proportional hazards model analysis indicated that age, bone marrow proliferation, proportion of tumor cells among nucleated cells, absolute neutrophil count, platelet count, and triglycerides and bilirubin levels significantly affected OS ( P<0.05). Multivariate COX regression analysis identified triglycerides and bilirubin levels as independent prognostic factors for OS. Conclusion:Aggressive natural killer-cell leukemia is a rare lymphoid malignancy with very poor prognosis. Tumor cells exhibit significant morphological variation, and bone marrow infiltration patterns are diverse. Accurate recognition, early diagnosis, and timely chemotherapy are critical to improving the prognosis of patients with ANKL.