Objective To evaluate the predictive ability and clinical application value of artificial intelligence (AI) systems in the benign and malignant differentiation and pathological type of pulmonary nodules, and to summarize clinical application experience. Methods A retrospective analysis was conducted on the clinical data of patients with pulmonary nodules admitted to the Department of Thoracic Surgery, Second Hospital of Lanzhou University, from February 2016 to February 2025. Firstly, pulmonary nodules were divided into benign and non-benign groups, and the discriminative abilities of AI systems and clinicians were compared. Subsequently, lung nodules reported as precursor glandular lesions (PGL), microinvasive adenocarcinoma (MIA), and invasive adenocarcinoma (IAC) in postoperative pathological results were analyzed, comparing the efficacy of AI systems and clinicians in predicting the pathological type of pulmonary nodules. Results In the analysis of benign/non-benign pulmonary nodules, clinical data from a total of 638 patients with pulmonary nodules were included, of which there were 257 males (10 patients and 1 patient of double and triple primary lesions, respectively) and 381 females (18 patients and 1 patient of double and triple primary lesions, respectively), with a median age of 55.0 (47.0, 61.0) years. Different lesions in the same patient were analyzed as independent samples. Univariate analysis of the two groups of variables showed that, except for nodule location, the differences in the remaining variables were statistically significant (P<0.05). Multivariate logistic regression analysis showed that age, nodule type (subsolid pulmonary nodule), average density, spicule sign, and vascular convergence sign were independent influencing factors for non-benign pulmonary nodules, among which age, nodule type (subsolid pulmonary nodule), spicule sign, and vascular convergence sign were positively correlated with non-benign pulmonary nodules, while average density was negatively correlated with the occurrence of non-benign pulmonary nodules. The area under the receiver operating characteristic curve (AUC) of the malignancy risk value given by the AI system in predicting non-benign pulmonary nodules was 0.811, slightly lower than the 0.898 predicted by clinicians. In the PGL/MIA/IAC analysis, clinical data from a total of 411 patients with pulmonary nodules were included, of which there were 149 males (8 patients of double primary lesions) and 262 females (17 patients of double primary lesions), with a median age of 56.0 (50.0, 61.0) years. Different lesions in the same patient were analyzed as independent samples. Univariate analysis results showed that, except for gender, nodule location, and vascular convergence sign, the differences in the remaining variables among the three groups of PGL, MIA, and IAC patients were statistically significant (P<0.05). Multinomial multivariate logistic regression analysis showed that the differences between the parameters in the PGL group and the MIA group were not statistically significant (P>0.05), and the maximum diameter and average density of the nodules were statistically different between the PGL and IAC groups (P<0.05), and were positively correlated with the occurrence of IAC as independent risk factors. The average AUC value, accuracy, recall rate, and F1 score of the AI system in predicting lung nodule pathological type were 0.807, 74.3%, 73.2%, and 68.5%, respectively, all better than the clinical physicians’ prediction of lung nodule pathological type indicators (0.782, 70.9%, 66.2%, and 63.7% respectively). The AUC value of the AI system in predicting IAC was 0.853, and the sensitivity, specificity, and optimal cutoff value were 0.643, 0.943, and 50.0%, respectively. Conclusion This AI system has demonstrated high clinical value in predicting the benign and malignant nature and pathological type of lung nodules, especially in predicting lung nodule pathological type, its ability has surpassed that of clinical physicians. With the optimization of algorithms and the adequate integration of multimodal data, it can better assist clinical physicians in formulating individualized diagnostic and treatment plans for patients with lung nodules.

Inflammatory bowel disease (IBD) is an idiopathic intestinal inflammatory condition with chronic and relapsing manifestations and is characterized by a disturbance in the interplay between the intestinal microbiota, the gut, and the brain. The microbiota-gut-brain axis involves interactions among the nervous system, the neuroendocrine system, the gut microbiota, and the host immune system. Increasing published data indicate that psychological stress exacerbates the severity of IBD due to its negative effects on the microbiota-gut-brain axis, including alterations in the stress response of the hypothalamic-pituitary-adrenal (HPA) axis, the balance between the sympathetic nervous system and vagus nerves, the homeostasis of the intestinal flora and metabolites, and normal intestinal immunity and permeability. Although the current evidence is insufficient, psychotropic agents, psychotherapies, and interventions targeting the microbiota-gut-brain axis show the potential to improve symptoms and quality of life in IBD patients. Therefore, further studies that translate recent findings into therapeutic approaches that improve both physical and psychological well-being are needed.
Humans ; Inflammatory Bowel Diseases/metabolism* ; Stress, Psychological/microbiology* ; Gastrointestinal Microbiome/physiology* ; Brain/metabolism* ; Hypothalamo-Hypophyseal System ; Pituitary-Adrenal System ; Animals

Objective The study aims to investigate the immunological functions of the nucleocapsid (N) protein of the novel coronavirus Omicron (BA.1, BA.2) and evaluate the differences among different N proteins of mutant strains in immunogenicity. Methods By aligning sequences, the mutation sites of the Omicron (BA.1, BA.2) N protein relative to prototype strain of the novel coronavirus (Wuhan-Hu-1) were determined. The pET-28a-N-Wuhan-Hu-1 plasmid was used as template to construct pET-28a-BA.1/BA.2-N through single point mutation or homologous recombination. The three kinds of N protein were expressed in prokaryotic system, purified through Ni-NTA affinity chromatography, and then immunized into mice. The titer and reactivity of the polyclonal antibody, as well as the expression level of IL-1β and IFN-γ in mouse spleen cells, were detected using indirect ELISA and Western blot assay. Results The constructed prokaryotic expression plasmids were successfully used to express the Wuhan-Hu-1 N, BA.1 N, and BA.2 N proteins in E.coli BL21(DE3) at 37 DegreesCelsius for 4 hours. The indirect ELISA test showed that the titers of polyclonal antibody prepared by three N proteins were all 1:51 200. All three N proteins can increase the expression of IFN-γ and IL-1β cytokines, but the effect of Omicron N protein in activing two cytokines was more obvious than that of Wuhan-Hu-1 N protein. Conclusion The study obtained three new coronavirus N proteins and polyclonal antibodies, and confirmed that mutations in the amino acid sites of the N protein can affect its immunogenicity. This provides a basis for developing rapid diagnostic methods targeting N protein of different novel coronavirus variants.
Animals ; Mice ; SARS-CoV-2/genetics* ; Coronavirus Nucleocapsid Proteins/immunology* ; Nucleocapsid Proteins/isolation & purification* ; COVID-19/immunology* ; Antibodies, Viral/immunology* ; Mice, Inbred BALB C ; Interferon-gamma/metabolism* ; Interleukin-1beta/metabolism* ; Female ; Escherichia coli/metabolism* ; Mutation ; Humans

BACKGROUND: Lung cancer is one of the most common malignant tumors worldwide and a major cause of cancer-related deaths. Early-stage lung cancer is often manifested as pulmonary nodules, and accurate assessment of the malignancy risk is crucial for prolonging survival and avoiding overtreatment. This study aims to construct a model based on image feature parameters automatically extracted by artificial intelligence (AI) to evaluate its effectiveness in predicting the malignancy of part-solid nodule (PSN). METHODS: This retrospective study analyzed 229 PSN from 222 patients who underwent pulmonary nodule resection at Lanzhou University Second Hospital between October 2020 and February 2025. According to pathological results, 45 cases of benign lesions and precursor glandular lesion were categorized into the non-malignant group, and 184 cases of pulmonary malignancies were categorized into the malignant group. All patients underwent preoperative chest computed tomography (CT), and AI software was used to extract imaging feature parameters. Univariate analysis was used to screen significant variables; variance inflation factor (VIF) was calculated to exclude highly collinear variables, and LASSO regression was further applied to identify key features. Multivariate Logistic regression was used to determine independent risk factors. Based on the selected variables, five models were constructed: Logistic regression, random forest, XGBoost, LightGBM, and support vector machine (SVM). Receiver operating characteristic (ROC) curves were used to assess the performance of the models. RESULTS: The independent risk factors for the malignancy of PSN include roughness (ngtdm), dependence variance (gldm), and short run low gray-level emphasis (glrlm). Logistic regression achieved area under the curves ( AUCs) of 0.86 and 0.89 in the training and testing sets, respectively, showing good performance. XGBoost had AUCs of 0.78 and 0.77, respectively, demonstrating relatively balanced performance, but with lower accuracy. SVM showed an AUC of 0.93 in the training set, which decreased to 0.80 in the testing set, indicating overfitting. LightGBM performed excellently in the training set with an AUC of 0.94, but its performance declined in the testing set, with an AUC of 0.88. In contrast, random forest demonstrated stable performance in both the training and testing sets, with AUCs of 0.89 and 0.91, respectively, exhibiting high stability and excellent generalizability. CONCLUSIONS The random forest model constructed based on independent risk factors demonstrated the best performance in predicting the malignancy of PSN and could provide effective auxiliary predictions for clinicians, supporting individualized treatment decisions.
.
Humans ; Male ; Female ; Lung Neoplasms/pathology* ; Middle Aged ; Retrospective Studies ; Artificial Intelligence ; Aged ; Tomography, X-Ray Computed ; Adult ; Solitary Pulmonary Nodule/diagnostic imaging* ; ROC Curve

Objective:To evaluate the clinical effectiveness and safety of fractional microneedle radiofrequency (RF), subsequently followed by narrowband intense pulsed light (IPL), in the treatment of facial photoaging.Methods:A retrospective analysis was performed on 50 female patients who underwent facial photodamage treatment at the Fifth People＇s Hospital of Suzhou from January to December 2021, with an average age of (40±8) years. Each patient received fractional microneedle RF therapy, subsequently followed by two sessions of narrowband IPL therapy at 500-600 nm, with a 4-week interval between treatments. Before and 4 weeks after the final treatment, skin parameters including wrinkles, redness, and sunspots were quantitatively assessed using the Visia skin image analyzer. Patients self-reported their satisfaction levels, and any adverse reactions were recorded.Results:All patients completed the prescribed treatment regimen. Post-treatment evaluations revealed marked improvements in facial skin, characterized by reduced wrinkles, enhanced skin smoothness, tighter contours, and lighter pigmentation spots. Specifically, the pre-treatment scores for wrinkles, sunspots, and redness were (25.6±10.2), (312.6±75.9), and (162.0±68.6) scores, respectively, which significantly decreased to (18.3±7.4), (261.2±82.7), and (129.7±60.1) scores four weeks post-treatment (all P<0.001). The patients＇ satisfaction levels were (6.6±1.2) scores. During treatment, all patients experienced mild erythema and edema, which resolved within 3-4 days. No serious adverse reactions, such as blistering, hyperpigmentation, or scarring, were observed. Conclusions:Fractional microneedle RF therapy, followed by narrowband IPL therapy, emerges as an effective and safe treatment option for facial photodamage, with minimal adverse reactions.

Objective:To investigate the efficacy and safety of separated R-CHOP in older patients with newly diagnosed diffuse large B-cell lymphoma(DLBCL).Methods:A total of 137 patients aged 65-80 years newly diagnosed with DLBCL between April 2013 and September 2022 at The First Affiliated Hospital of Zhengzhou University were enrolled.The patients were assigned into separated R-CHOP,full-dose R-CHOP,and reduced R-CHOP-like groups based on their different chemotherapy regimens.All individuals were treated in 21-day cycles for 4-8 cycles.The short-term and long-term efficacies and adverse reactions of the treatments were compared among the three groups,and factors influencing progression-free survival(PFS)and overall survival(OS)were analyzed.Results:The overall response rates(ORR)of patients in the separated R-CHOP,full-dose R-CHOP,and reduced R-CHOP-like groups were 89.7%,90.3%,and 86.1%,respectively,with no significant differences among them.The complete respond rate(CRR)of the separated R-CHOP group(64.1%)was significantly higher than that of the reduced R-CHOP-like group(33.3%)(P=0.008)but not significantly different from that of the full-dose R-CHOP group(66.1%).Survival curve analysis revealed no significant differences in PFS and OS between the separated and full-dose R-CHOP groups.Although the separated R-CHOP group showed improved PFS compared with the reduced R-CHOP-like group(P=0.036),there was no statistical difference in OS between these two groups.Multivariate analysis revealed that the international prognostic index(IPI)and separated R-CHOP had significant effects on PFS in patients with DLBCL(all P<0.05),whereas only IPI had a significant effect on OS(P<0.001).The incidence of leukopenia and grade 3-4 leukopenia in the separated R-CHOP group was significantly lower than that in the full-dose R-CHOP group(P=0.007,P=0.012),but there was no significant difference with the reduced R-CHOP-like group in this regard.Conclusions:In older patients with newly diagnosed DLBCL,separated R-CHOP showed good efficacy both in the short and long terms and had acceptable safety and tolerability profiles.

Purpose To design PCR combined probes u-sing TaqMan technology to detect the expression of major driver genes in a variety of soft tissue sarcomas at one time,and to dis-cuss whether the combined probes can better assist clinicopatho-logical diagnosis based on histological features and FISH results.Methods Our research group designed 32 pairs of fusion gene probes related to soft tissue sarcoma based on TaqMan tech-nique,involving 10 types of sarcoma.The histopathological specimens of 70 patients with common fusion gene soft tissue sarcoma in our hospital were examined by fusion gene combina-tion,and the histopathological specimens of 30 patients with oth-er soft tissue sarcoma without fusion gene were set as controls.Individual common sarcoma types were analyzed with FISH probe detection.At the same time,the detection performance of the combined probe was evaluated by various methods.Results The soft tissue sarcoma-related fusion gene probe designed by our research group was used to detect the confirmed soft tissue sarcomas,and the results showed that the highest sensitivity was 100％.Among the three types of tumors,protuberant dermatofi-brosarcoma,synovial sarcoma and mucinous liposarcoma were verified by FISH,and the coincidence rate of the two methods was high,with no statistical significance(P＞0.05).The re-sults of interlot and intralot reproducibility of protuberous derma-tofibrosarcoma,mucinous liposarcoma and synovial sarcoma were consistent.Three different concentration limits were used to de-tect the positive plasmid of all the fused gene RNA,and 25 cop-ies/μL was the lowest concentration limit.Conclusion Com-bined with the pathological diagnosis results,TaqMan technology can be used to design PCR combined probes for soft tissue sarco-ma,which have high sensitivity and high specificity and good methodological performance,and meet the needs of primary medical institutions for one-time and rapid auxiliary pathological diagnosis of common soft tissue sarcoma.It provides a rapid and reliable method for the detection of multiple fusion genes in clin-ical soft tissue sarcoma.

Objective:To explore the real experience and needs of lymphoma patients during chimeric antigen receptor T cell (CAR-T) therapy, so as to provide guidance for developing nursing intervention strategies.Methods:The phenomenological research method was used to conduct semi-structured interviews with 13 lymphoma patients receiving CAR-T therapy, and the interview data was analyzed using the Colaizzi 7-step analysis method.Results:Three themes were extracted, including diverse symptom perception (systemic symptoms such as fever and fatigue, as well as multiple system symptoms such as breathing, digestion, and nerves), complex emotional experience interweaving (coexistence of hope and doubt, changes and loss of environmental adaptability, and a variety of negative emotions), and urgent social needs (treatment related information needs, desire for medical and nursing staff's attention and help, family emotional support, and home rehabilitation continuing care) .Conclusions:Lymphoma patients experience significant physical and mental pain during CAR-T therapy. Medical and nursing staff should provide patients with comprehensive support to help them identify and improve physical discomfort symptoms, reduce psychological burden, meet physical and mental needs, and promote disease recovery.

A novel amide alkaloid,bursatamide A(1),featuring an unprecedented propyl-hexahydronaphthalene carbon frame-work,was isolated from the infrequently studied sea hare Bursatella leachi,alongside a new 3-phenoxypropanenitrile alkaloid,bursatellin B(2),and twelve known compounds.The structures of 1 and 2 were elucidated through comprehensive spectroscopic data analyses,while their relative and absolute configurations(ACs)were established through total synthesis and a series of quantum chem-ical calculations,including calculated electronic circular dichroism(ECD)spectra,optical rotatory dispersion(ORD)methods,and DP4+probability analyses.Bursatamide A(1)demonstrated inhibitory effects against the human pathogenic bacteria Listeria monocyt-ogenes and Vibrio cholerae.Erythro-bursatellin B(21),a diastereoisomer of 2,exhibited notable antibacterial activity against the fish pathogenic bacterium Streptococcus parauberis FP KSP28,with an MIC90 value of 0.0472 μg·mL-1.

Objective:To investigate the value of machine learning model based on MRI in predicting the abundance of tumor infiltrating CD 8+ T cell and prognosis of pancreatic cancer patients. Methods:The clinical data of 156 patients with pathological confirmed pancreatic cancer who underwent pre-operative MRI within 7 days before surgery in the First Affiliated Hospital of Naval Medical University from January 2017 to April 2018 was retrospectively analyzed. According to the international consensus on the predictive model, a total of 116 patients from January to December 2017 were included in the training set, and a total of 40 patients from January to April 2018 were included in the validation set. With the overall survival of patients as the outcome variable, X-Tile software was used to obtain cut-off values of the percentage of CD 8+ T cells, and all patients were divided into CD 8+ T-high and -low groups. The clinical, pathological and radiological features were compared between two groups. 3D slicer software was used to draw the region of interest in each layer of the primary MR T 1- and T 2-weighted imaging, arterial phase, portal venous phase, and delayed phase images for tumor segmentation. Python package was applied to extract the radiomics features of pancreatic tumors after segmentation and the extracted features were reduced and chosen using the least absolute shrinkage and selection operator (Lasso) logistic regression algorithm. Lasso logistic regression formula was applied to calculate the rad-score. The extreme gradient boosting (XGBoost) were used to construct the machine learning predicted model. The models′ performances were determined by area under the ROC curve (AUC), sensitivity, specificity, accuracy, positive predictive value, and negative predictive value. Results:The cut-off value of the CD 8+ T-cell level was 19.09% as determined by the X-tile program. Patients in the high CD 8+ T cell group had a longer median survival than those in the low CD 8+ T cell group (25.51 month vs 22.92 month, P=0.007). The T stage in the training set and tumor size in the validation set significantly differed between the groups (all P value <0.05). A total of 1 409 radiomics features were obtained, and 19-selected features associated with the level of CD 8+ T cell were determined after being reduced by the Lasso logistic regression algorithm. The rad-score was significantly lower in the CD 8- high group (median: -0.43; range: -1.55 to 0.65) than the CD 8- low group (median: 0.22; range: -0.68 to 2.54, P<0.001). The prediction model combined the radiomics features and tumor size. In the training set, the AUC, sensitivity, specificity, accuracy, and positive and negative predictive value were 0.90 (95% CI 0.85-0.95), 75.47%, 90.48%, 0.84, 0.87, and 0.81. In the validation set, the AUC, sensitivity, specificity, accuracy, and positive and negative predictive value were 0.79 (95% CI 0.63-0.96), 90.00%, 80.00%, 0.85, 0.82, and 0.89. The predictive model can accurately distinguish patients with high and low CD 8+ T cells in pancreatic cancer. Conclusions:The radiomics-based machine learning model is valuable in predicting the CD 8+ T cells infiltrating level in pancreatic cancer patients, which could be useful in identifying potential patients who can benefit from immunotherapies.