BACKGROUND: The clinical impact of post-percutaneous coronary intervention (PCI) quantitative flow ratio (QFR) in patients treated with PCI for chronic total occlusion (CTO) was still undetermined. METHODS: All CTO vessels treated with successful anatomical PCI in patients from PANDA III trial were retrospectively measured for post-PCI QFR. The primary outcome was 2-year vessel-oriented composite endpoints (VOCEs, composite of target vessel-related cardiac death, target vessel-related myocardial infarction, and ischemia-driven target vessel revascularization). Receiver operator characteristic curve analysis was conducted to identify optimal cutoff value of post-PCI QFR for predicting the 2-year VOCEs, and all vessels were stratified by this optimal cutoff value. Cox proportional hazards models were employed to calculate the hazard ratio (HR) with 95% CI. RESULTS: Among 428 CTO vessels treated with PCI, 353 vessels (82.5%) were analyzable for post-PCI QFR. 31 VOCEs (8.7%) occurred at 2 years. Mean value of post-PCI QFR was 0.92 ± 0.13. Receiver operator characteristic curve analysis shown the optimal cutoff value of post-PCI QFR for predicting 2-year VOCEs was 0.91. The incidence of 2-year VOCEs in the vessel with post-PCI QFR < 0.91 (n = 91) was significantly higher compared with the vessels with post-PCI QFR ≥ 0.91 (n = 262) (22.0% vs. 4.2%, HR = 4.98, 95% CI: 2.32-10.70). CONCLUSIONS Higher post-PCI QFR values were associated with improved prognosis in the PCI practice for coronary CTO. Achieving functionally optimal PCI results (post-PCI QFR value ≥ 0.91) tends to get better prognosis for patients with CTO lesions.

Compared to traditional machine learning algorithms,which often suffer from low feature extraction efficiency,insufficient nonlinear pattern recognition capabilities and slow training speeds,the broad learning system(BLS)enhances the learning ability and efficiency by horizontally expanding the network structure.BLS offers advantages such as a simple structure,fast training speed,and strong generalization capabilities.While BLS has demonstrated potential in various fields,but its application in identification of complex samples has not been fully explored.This research investigated the feasibility of using BLS algorithm for identification of complex samples based on physicochemical indicators.Using the iris,wine,and breast cancer datasets,the length and width of petals and sepals of iris flowers,the physicochemical properties of wine,and the nuclear characteristics of breast cancer cells were used as input variables to establish BLS models for identifying iris species,wine varieties,and benign versus malignant nucleus.The model performance was evaluated by confusion matrices,accuracy,and runtime.Compared with partial least squares-discriminant analysis(PLS-DA),soft independent modeling of class analogies(SIMCA),and artificial neural networks(ANN),the results indicated that BLS demonstrated significant advantages in computational efficiency and recognition accuracy.Thus,BLS was an efficient and reliable method for identification of complex samples.

The control and utilization of microorganisms in space-based animal culture constitute a pivotal challenge underpinning research domains such as space life sciences and extraterrestrial life-support system.This paper systematically examines the origins,transmission routes,and latent risks of microbial contamination in space-based animal culture facilities.A comprehensive analysis is conducted on the advancements in on-orbit implementation of microbial containment strategies,including physical filtration systems,antimicrobial surface coatings,and environmental parameter optimization.Additionally,the study evaluates the prospective applications of probiotic consortia and functionally engineered microorganisms in enhancing animal welfare,stabilizing biosphere conditions,and enabling closed-loop waste recycling.Notably,this work highlights the paradigm shift from reactive microbial suppression to proactive microbiome engineering in space-based animal husbandry,thereby establishing a theoretical framework for sustainable development of space-based animal culture.

Objective:To analyze the efficacy of phantom-less quantitative computer tomography (PL-QCT) for the diagnosis of osteoporosis in patients with lumbar degenerative diseases.Methods:From October 2021 to October 2023, a total of 1 248 patients with lumbar degenerative disease who did not receive anti-osteoporosis treatment in the Department of Spine Surgery, Tianjin Hospital were retrospectively analyzed. There were 520 males and 728 females, aged 62.31±9.37 years (range, 40-87 years), height 1.66±0.08 m (range, 1.43-1.89 m), weight 69.04±8.27 kg (range, 49-93 kg). The mean body mass index was 26.11±3.67 kg/m 2 (range, 14.40-37.11 kg/m 2). Dual-energy X-ray absorptiometry (DXA) and PL-QCT were used to diagnose osteoporosis, and the detection rates of the two diagnostic methods were compared. The receiver operating characteristic (ROC) curve of PL-QCT for the diagnosis of osteoporosis was drawn, the area under the curve (AUC) and 95% confidence interval (CI), sensitivity and specificity were calculated. Results:Among 1 248 patients with lumbar degenerative diseases, 626 (50.2%) were diagnosed as osteoporosis by PL-QCT, 423(33.9%) were diagnosed by spine DXA, 488(39.1%) were diagnosed by hip DXA and 539 patients(43.2%) were diagnosed by dual-site DXA. The detection rate of osteoporosis of PL-QCT was higher than that of spine DXA (χ 2=193.557, P<0.001), hip DXA (χ 2=322.201, P<0.001) and dual-site DXA (χ 2=94.683, P<0.001), and the difference was statistically significant. Taking the diagnostic results of spinal DXA for osteoporosis as a reference, the ROC curve of PL-QCT for the diagnosis of osteoporosis showed a sensitivity of 79%, a specificity of 81%, and an AUC and 95% CI of 0.82(0.79, 0.85). Taking the diagnostic results of hip DXA for osteoporosis as a reference, the ROC curve of PL-QCT for the diagnosis of osteoporosis showed a sensitivity of 85%, a specificity of 55%, and an AUC and 95% CI of 0.75(0.71, 0.78). Taking the diagnostic results of two-site DXA for osteoporosis as a reference, the ROC curve of PL-QCT for the diagnosis of osteoporosis showed a sensitivity of 72%, a specificity of 75%, and an AUC and 95% CI of 0.81(0.78, 0.83). Conclusion:Compared with DXA, PL-QCT has a higher detection rate of osteoporosis in patients with degenerative lumbar spine disease and good diagnostic efficacy.

Objective:To investigate the clinical efficacy of lumbar lateral interbody fusion (LLIF) versus posterior lumbar interbody fusion (PLIF) in the treatment of severe lumbar spinal stenosis.Methods:The data of patients with severe lumbar spinal stenosis who underwent LLIF or PLIF from February 2019 to December 2023 were retrospectively analyzed. There were 30 patients in the LLIF group, 10 males and 20 females, aged 62.7±5.6 years (range, 53-74 years), including 21 cases of single segment and 9 cases of double segment. There were 46 patients in the PLIF group, including 20 males and 26 females, aged 63.2±8.4 years (range, 43-75 years), 40 cases of single segment and 6 cases of double segment. The visual analogue scale (VAS), Oswestry disability index (ODI), intervertebral space height, intervertebral foramen height and postoperative complications were compared between the two groups.Results:All patients were followed up for an average of 21.3±6.4 months (range, 12-32 months). The intraoperative blood loss in the LLIF group was 112.2±76.9 ml, which was significantly lower than 193.9±88.2 ml in the PLIF group ( P<0.05). The VAS scores of back pain and leg pain after operation were significantly lower than those before operation in the two groups ( P<0.05). There was no statistically significant difference between groups in back pain VAS scores at preoperative, 6 months postoperative, and final follow-up ( P>0.05); the back pain VAS score at 1 month postoperatively in the LLIF group was 1.6±1.2, which was less than 2.8±0.7 in the PLIF group ( P<0.05). There was no statistically significant difference between groups in leg pain VAS scores at preoperative, 1 month postoperative, and 6 months postoperative ( P>0.05); the leg pain VAS score at the final follow-up in the LLIF group was 1.2±1.5, which was smaller than 1.8±1.0 in the PLIF group ( P<0.05). The postoperative ODI was smaller than the preoperative one in both groups, and the difference was statistically significant ( P<0.05); the preoperative, 1-month postoperative, 6-month postoperative, and final follow-up ODIs in the LLIF group were 45.7%±16.0%, 17.9%±12.0%, 16.2%±11.6%, and 15.7%±11.7%, and those in the PLIF group were 47.9%±15.4%, 20.1%±9.3%, 16.9%±10.6%, and 14.6%±11.0% in the PLIF group, and the difference between the groups was not statistically significant ( P>0.05). The preoperative intervertebral space height in the LLIF group was 10.6±2.0 mm, which was smaller than that in the PLIF group 11.8±2.2 mm ( P<0.05). The intervertebral space heights in the immediate postoperative period and at the final follow-up were 13.3±2.3 mm and 12.3±2.2 mm in the LLIF group and 13.7±1.7 mm and 13.0±1.9 mm in the PLIF group ( P>0.05). The preoperative intervertebral foraminal height in the LLIF group was 18.0±3.2 mm, which was smaller than that of 19.7±2.4 mm in the PLIF group ( P<0.05); the intervertebral foraminal heights in the immediate postoperative period and at the final follow-up were 21.4±2.5 mm and 20.2±2.4 mm in the LLIF group, and in the PLIF group were 20.7±2.4 mm and 19.7±2.6 mm in the PLIF group ( P>0.05). In the LLIF group, 2 cases had femoral nerve injury and 2 cases had transient back pain after operation. There were 2 cases of cerebrospinal fluid leakage, 1 case of screw loosening, and 2 cases of deep vein thrombosis in the PLIF group. In the PLIF group, 2 patients underwent revision, including 1 case due to cage displacement and 1 case due to screw malposition. The fusion settling rate was 21% (8/39) in the LLIF group and 12% (6/52) in the PLIF group ( P>0.05). Conclusion:Both LLIF and PLIF can effectively restore the intervertebral height, improve the lumbar function and the symptoms of back and leg pain in the treatment of severe lumbar spinal stenosis.

Objective:To develop and validate a combined model integrating radiomics, dosiomics, and clinical parameters based on CT simulation and dosimetric images in order to predict the occurrence of radiation pneumonitis (RP) in patients with non-small cell lung cancer (NSCLC).Methods:A retrospective study was conducted on the clinic data of 143 NSCLC patients who received radiotherapy at the Affiliated Hospital of Jining Medical University from January 2016 to December 2022. Patients were randomly stratified into a training group ( n = 100) and an internal validation group ( n = 43) at a 7∶3 ratio. Moreover, clinic data were collected from 34 NSCLC patients who received radiotherapy at the Jining Cancer Hospital between January 2019 and December 2022 as an external validation group. All three groups (the training group, internal validation, and external validation groups) were further categorized into two groups based on the RP severity (i.e., RP ≥ grade 2 and RP < grade 2). Their radiotherapy dose, CT simulation, and 3D dose distribution images were collected. Then, the total lung minus planning target volume (TL-PTV) was defined as the region of interest (ROI) for radiomics and dosiomic feature extraction, followed by feature dimensionality reduction. Consequently, key features associated with RP were determined. Four predictive models were developed using machine learning approaches (especially multilayer perceptron, MLP): a clinical model (CM), a radiomics model (RM), a dosiomics model (DM), and a radiomics and dosiomics nomogram (RDN), with a nomogram subsequently constructed. Ultimately, the performance and clinical feasibility of these models were assessed using receiver operating characteristic (ROC), area under the curve (AUC), and decision curve analysis (DCA). Results:A total of 1 834 radiomic features and 1 834 dosiomic features were extracted. Using the occurrence of RP ≥ grade 2 as the marker variable, 14 radiomic features, 15 dosiomic features, and three clinical features were selected from the training group to construct the prediction models (CM, RM, DM, and RDN). The performance and generalizability of these models were subsequently validated in both the internal validation and external validation groups. Specifically, the RDN exhibited AUCs of 0.915 (95% CI: 0.852-0.978), 0.879 (95% CI: 0.777-0.982), and 0.838 (95% CI: 0.701-0.975) in the three groups, respectively. A nomogram was established for RDN by integrating the radiomics score (R-score), dosiomics score (D-score), mean lung dose (MLD), V20, and V30. This nomogram allowed for individualized risk estimation of RP and facilitated personalized radiotherapy planning. Conclusions:The RDN model that is developed based on CT simulation and 3D dose distribution images and integrates radiomics, dosiomics, and clinical features can effectively predict the RP risk of NSCLC patients. The integration of multidimensional data contributes to the formation of the optimal predictive model, offering guidance for clinicians.

Objective:To evaluate the efficacy and safety of nebulized inhalation of recombinant human interferon (IFN) α1b injection in the treatment of respiratory syncytial virus (RSV) associated lower respiratory tract infections (pneumonia and bronchiolitis) in children.Methods:A randomized, double-blind, parallel, placebo-controlled add-on design was used.Children with pneumonia or bronchiolitis aged 2 months to 5 years who tested positive for RSV antigen within 72 hours of onset from 30 clinical trial sites including Beijing Children′s Hospital, Capital Medical University between February 2021 and December 2022 were included in this study and randomly divided into 2 groups at a ratio of 1∶1 based on a stratified-block method.Both groups received basic treatments such as cough control, asthma relieving, expectorant treatment, fever reduction, oxygen therapy, etc.The experimental group received additional nebulized inhalation of IFN α1b injection at a dose of 2.0 μg/(kg·time), twice a day.The control group received nebulized inhalation of placebo twice a day.Clinical efficacy was evaluated based on indicators such as the duration of clinical symptoms and signs, and the Kaplan-Meier method was used to calculate the median and 95% CI of the duration of clinical symptoms and signs.The Log-rank test was used to compared data between groups.Safety was assessed through the incidence of adverse reactions and laboratory tests, and the Chi-square test was used to analyze the difference between groups. Results:There were 123 children in the experimental group and 122 children in the control group.The median durations of all the 5 clinical symptoms and signs [including shortness of breath, wheezing, dyspnea (visible retractions), decreased transcutaneous oxygen saturation, and abnormal mental state] in the experimental group after treatment were slightly shortened than those in the control group [2.7 d(95% CI: 1.9-3.0 d)] vs.[2.9 d(95% CI: 2.6-3.6 d), P=0.027].The improvement in dyspnea (retractions) was especially pronounced in the experimental group, with a relief rate of 50.0% (0, 100%) on the first day of administration[compared with 0 (0, 50.0%) in the control group ( Z=2.002, P=0.025)].The median duration of dyspnea in the experimental group was nearly 1 day shorter than that in the control group [1.0 d(95% CI: 0.7-1.7 d) vs.1.8 d(95% CI: 1.0-2.5 d), P=0.046].There were no significant difference in hospital stay [6.0(5.0, 8.0) d vs.6.5(5.0, 8.0) d, Z=0.675, P=0.500], oxygen therapy duration [32.0(14.0, 96.3) h vs.39.0 (24.0, 83.2) h, Z=0.094, P=0.925], the recovery rate from clinical symptoms during treatment [(105/106, 99.1%) vs.(96/101, 95.0%)], and recurrence rate [(0/106, 0) vs.(2/101, 2.0%)] between the 2 groups (all P>0.05).However, the above-mentioned four indicators in the experimental group showed a trend of clinical benefits.The quantitative virus detection results showed that the RSV viral load in both groups decreased after treatment compared to before treatment.After 2 days of treatment, the decline rate of RSV viral load from the baseline was 0.90 lg copies/(mL·d) in the experimental group and 0.25 lg copies/(mL·d)in the control group, with a statistically significant difference ( P<0.05).Furthermore, there was no statistically significant difference in the incidence of adverse reactions between the 2 groups ( P>0.05).Importantly, no drug-related serious adverse reactions occurred in both groups. Conclusions:The nebulized inhalation therapy of IFN α1b demonstrates efficacy and safety in treating pediatric RSV associated lower respiratory tract infections.It particularly offers outstanding clinical therapeutic value for severe children.

Objective:To analyze the efficacy of phantom-less quantitative computer tomography (PL-QCT) for the diagnosis of osteoporosis in patients with lumbar degenerative diseases.Methods:From October 2021 to October 2023, a total of 1 248 patients with lumbar degenerative disease who did not receive anti-osteoporosis treatment in the Department of Spine Surgery, Tianjin Hospital were retrospectively analyzed. There were 520 males and 728 females, aged 62.31±9.37 years (range, 40-87 years), height 1.66±0.08 m (range, 1.43-1.89 m), weight 69.04±8.27 kg (range, 49-93 kg). The mean body mass index was 26.11±3.67 kg/m 2 (range, 14.40-37.11 kg/m 2). Dual-energy X-ray absorptiometry (DXA) and PL-QCT were used to diagnose osteoporosis, and the detection rates of the two diagnostic methods were compared. The receiver operating characteristic (ROC) curve of PL-QCT for the diagnosis of osteoporosis was drawn, the area under the curve (AUC) and 95% confidence interval (CI), sensitivity and specificity were calculated. Results:Among 1 248 patients with lumbar degenerative diseases, 626 (50.2%) were diagnosed as osteoporosis by PL-QCT, 423(33.9%) were diagnosed by spine DXA, 488(39.1%) were diagnosed by hip DXA and 539 patients(43.2%) were diagnosed by dual-site DXA. The detection rate of osteoporosis of PL-QCT was higher than that of spine DXA (χ 2=193.557, P<0.001), hip DXA (χ 2=322.201, P<0.001) and dual-site DXA (χ 2=94.683, P<0.001), and the difference was statistically significant. Taking the diagnostic results of spinal DXA for osteoporosis as a reference, the ROC curve of PL-QCT for the diagnosis of osteoporosis showed a sensitivity of 79%, a specificity of 81%, and an AUC and 95% CI of 0.82(0.79, 0.85). Taking the diagnostic results of hip DXA for osteoporosis as a reference, the ROC curve of PL-QCT for the diagnosis of osteoporosis showed a sensitivity of 85%, a specificity of 55%, and an AUC and 95% CI of 0.75(0.71, 0.78). Taking the diagnostic results of two-site DXA for osteoporosis as a reference, the ROC curve of PL-QCT for the diagnosis of osteoporosis showed a sensitivity of 72%, a specificity of 75%, and an AUC and 95% CI of 0.81(0.78, 0.83). Conclusion:Compared with DXA, PL-QCT has a higher detection rate of osteoporosis in patients with degenerative lumbar spine disease and good diagnostic efficacy.

Objective:To investigate the clinical efficacy of lumbar lateral interbody fusion (LLIF) versus posterior lumbar interbody fusion (PLIF) in the treatment of severe lumbar spinal stenosis.Methods:The data of patients with severe lumbar spinal stenosis who underwent LLIF or PLIF from February 2019 to December 2023 were retrospectively analyzed. There were 30 patients in the LLIF group, 10 males and 20 females, aged 62.7±5.6 years (range, 53-74 years), including 21 cases of single segment and 9 cases of double segment. There were 46 patients in the PLIF group, including 20 males and 26 females, aged 63.2±8.4 years (range, 43-75 years), 40 cases of single segment and 6 cases of double segment. The visual analogue scale (VAS), Oswestry disability index (ODI), intervertebral space height, intervertebral foramen height and postoperative complications were compared between the two groups.Results:All patients were followed up for an average of 21.3±6.4 months (range, 12-32 months). The intraoperative blood loss in the LLIF group was 112.2±76.9 ml, which was significantly lower than 193.9±88.2 ml in the PLIF group ( P<0.05). The VAS scores of back pain and leg pain after operation were significantly lower than those before operation in the two groups ( P<0.05). There was no statistically significant difference between groups in back pain VAS scores at preoperative, 6 months postoperative, and final follow-up ( P>0.05); the back pain VAS score at 1 month postoperatively in the LLIF group was 1.6±1.2, which was less than 2.8±0.7 in the PLIF group ( P<0.05). There was no statistically significant difference between groups in leg pain VAS scores at preoperative, 1 month postoperative, and 6 months postoperative ( P>0.05); the leg pain VAS score at the final follow-up in the LLIF group was 1.2±1.5, which was smaller than 1.8±1.0 in the PLIF group ( P<0.05). The postoperative ODI was smaller than the preoperative one in both groups, and the difference was statistically significant ( P<0.05); the preoperative, 1-month postoperative, 6-month postoperative, and final follow-up ODIs in the LLIF group were 45.7%±16.0%, 17.9%±12.0%, 16.2%±11.6%, and 15.7%±11.7%, and those in the PLIF group were 47.9%±15.4%, 20.1%±9.3%, 16.9%±10.6%, and 14.6%±11.0% in the PLIF group, and the difference between the groups was not statistically significant ( P>0.05). The preoperative intervertebral space height in the LLIF group was 10.6±2.0 mm, which was smaller than that in the PLIF group 11.8±2.2 mm ( P<0.05). The intervertebral space heights in the immediate postoperative period and at the final follow-up were 13.3±2.3 mm and 12.3±2.2 mm in the LLIF group and 13.7±1.7 mm and 13.0±1.9 mm in the PLIF group ( P>0.05). The preoperative intervertebral foraminal height in the LLIF group was 18.0±3.2 mm, which was smaller than that of 19.7±2.4 mm in the PLIF group ( P<0.05); the intervertebral foraminal heights in the immediate postoperative period and at the final follow-up were 21.4±2.5 mm and 20.2±2.4 mm in the LLIF group, and in the PLIF group were 20.7±2.4 mm and 19.7±2.6 mm in the PLIF group ( P>0.05). In the LLIF group, 2 cases had femoral nerve injury and 2 cases had transient back pain after operation. There were 2 cases of cerebrospinal fluid leakage, 1 case of screw loosening, and 2 cases of deep vein thrombosis in the PLIF group. In the PLIF group, 2 patients underwent revision, including 1 case due to cage displacement and 1 case due to screw malposition. The fusion settling rate was 21% (8/39) in the LLIF group and 12% (6/52) in the PLIF group ( P>0.05). Conclusion:Both LLIF and PLIF can effectively restore the intervertebral height, improve the lumbar function and the symptoms of back and leg pain in the treatment of severe lumbar spinal stenosis.

Objective:To develop and validate a combined model integrating radiomics, dosiomics, and clinical parameters based on CT simulation and dosimetric images in order to predict the occurrence of radiation pneumonitis (RP) in patients with non-small cell lung cancer (NSCLC).Methods:A retrospective study was conducted on the clinic data of 143 NSCLC patients who received radiotherapy at the Affiliated Hospital of Jining Medical University from January 2016 to December 2022. Patients were randomly stratified into a training group ( n = 100) and an internal validation group ( n = 43) at a 7∶3 ratio. Moreover, clinic data were collected from 34 NSCLC patients who received radiotherapy at the Jining Cancer Hospital between January 2019 and December 2022 as an external validation group. All three groups (the training group, internal validation, and external validation groups) were further categorized into two groups based on the RP severity (i.e., RP ≥ grade 2 and RP < grade 2). Their radiotherapy dose, CT simulation, and 3D dose distribution images were collected. Then, the total lung minus planning target volume (TL-PTV) was defined as the region of interest (ROI) for radiomics and dosiomic feature extraction, followed by feature dimensionality reduction. Consequently, key features associated with RP were determined. Four predictive models were developed using machine learning approaches (especially multilayer perceptron, MLP): a clinical model (CM), a radiomics model (RM), a dosiomics model (DM), and a radiomics and dosiomics nomogram (RDN), with a nomogram subsequently constructed. Ultimately, the performance and clinical feasibility of these models were assessed using receiver operating characteristic (ROC), area under the curve (AUC), and decision curve analysis (DCA). Results:A total of 1 834 radiomic features and 1 834 dosiomic features were extracted. Using the occurrence of RP ≥ grade 2 as the marker variable, 14 radiomic features, 15 dosiomic features, and three clinical features were selected from the training group to construct the prediction models (CM, RM, DM, and RDN). The performance and generalizability of these models were subsequently validated in both the internal validation and external validation groups. Specifically, the RDN exhibited AUCs of 0.915 (95% CI: 0.852-0.978), 0.879 (95% CI: 0.777-0.982), and 0.838 (95% CI: 0.701-0.975) in the three groups, respectively. A nomogram was established for RDN by integrating the radiomics score (R-score), dosiomics score (D-score), mean lung dose (MLD), V20, and V30. This nomogram allowed for individualized risk estimation of RP and facilitated personalized radiotherapy planning. Conclusions:The RDN model that is developed based on CT simulation and 3D dose distribution images and integrates radiomics, dosiomics, and clinical features can effectively predict the RP risk of NSCLC patients. The integration of multidimensional data contributes to the formation of the optimal predictive model, offering guidance for clinicians.