Exploration of the correlation between facet joints cross-sectional area asymmetry and cervical disc herniation.

PURPOSE: To evaluate the association between facet joints cross-sectional area asymmetry (FCAA) and cervical intervertebral disc herniation (CDH). METHODS: Overall, we retrospectively recruited 390 consecutive patients with CDH who underwent surgical treatment at our institution and 50 normal participants. Clinical variables and radiological findings related to CDH were collected. RESULTS: Patients with CDH were more likely to have a higher absolute value of the facet asymmetry factor (FAF) (p < .001), in which the FAF value of the left group was significantly higher than the other groups (p < .001) and the right group was lower than the central group (p < .001). 9.62% (C3/4), 12.19% (C4/5), 8.70% (C5/6), and 8.14% (C6/7) were determined as cutoff values for each variable that maximized sensitivity and specificity. Furthermore, multivariate analysis showed that cross-sectional area asymmetry of the facet joint (FCAA) was an independent risk factor for the occurrence of CDH. Also, the Chi-square test showed a significant difference in the distribution of the degeneration classification of the disc between the facet-degenerated group and the nondegenerated group at C5/6 (p = 0.026) and C6/7 (p = 0.005) in the facet asymmetry (FA) group. CONCLUSIONS: FCAA is evaluated as an independent risk factor for CDH and associated with the orientation of disc herniation. And facet joint orientation may also play a role in cervical spine degeneration rather than facet joint tropism.

Optimizing prediction accuracy for early recurrent lumbar disc herniation with a directional mutation-guided SVM model.

Percutaneous endoscopic lumbar discectomy (PELD) is one of the main means of minimally invasive spinal surgery, and is an effective means of treating lumbar disc herniation, but its early recurrence is still difficult to predict. With the development of machine learning technology, the auxiliary model based on the prediction of early recurrent lumbar disc herniation (rLDH) and the identification of causative risk factors have become urgent problems in current research. However, the screening ability of current models for key factors affecting the prediction of rLDH, as well as their predictive ability, needs to be improved. Therefore, this paper presents a classification model that utilizes wrapper feature selection, developed through the integration of an enhanced bat algorithm (BDGBA) and support vector machine (SVM). Among them, BDGBA increases the population diversity and improves the population quality by introducing directional mutation strategy and guidance-based strategy, which in turn allows the model to secure better subsets of features. Furthermore, SVM serves as the classifier for the wrapper feature selection method, with its classification prediction results acting as a fitness function for the feature subset. In the proposed prediction method, BDGBA is used as an optimizer for feature subset filtering and as an objective function for feature subset evaluation based on the classification results of the support vector machine, which improves the interpretability and prediction accuracy of the model. In order to verify the performance of the proposed method, this paper proves the performance of the model through global optimization experiments and prediction experiments on real data sets. The accuracy of the proposed rLDH prediction model is 93.49% and sensitivity is 88.33%. The experimental results show that Level of herniated disk, Modic change, Disk height, Disk length, and Disk width are the key factors for predicting rLDH, and the proposed method is an effective auxiliary diagnosis method.

Comparative study of two models predicting the risk of deep vein thrombosis progression in spinal trauma patients after operation.

OBJECTIVE: Patients with preoperative deep vein thrombosis (DVT) exhibit a notable incidence of postoperative deep vein thrombosis progression (DVTp), which bears a potential for silent, severe consequences. Consequently, the development of a predictive model for the risk of postoperative DVTp among spinal trauma patients is important. METHODS: Data of 161 spinal traumatic patients with preoperative DVT, who underwent spine surgery after admission, were collected from our hospital between January 2016 and December 2022. The least absolute shrinkage and selection operator (LASSO) combined with multivariable logistic regression analysis was applied to select variables for the development of the predictive logistic regression models. One logistic regression model was formulated simply with the Caprini risk score (Model A), while the other model incorporated not only the previously screened variables but also the age variable (Model B). The model's capability was evaluated using sensitivity, specificity, positive predictive value, negative predictive value, accuracy, F1 score, and receiver operating characteristic (ROC) curve. Nomograms simplified and visually presented Model B for the clinicians and patients to understand the predictive model. The decision curve was used to analyze the clinical value of Model B. RESULTS: A total of 161 DVT patients were enrolled in this study. Postoperative DVTp occurred in 48 spinal trauma patients, accounting for 29.81% of the total patient enrolled. Model A inadequately predicted postoperative DVTp in spinal trauma patients, with ROC AUC values of 0.595 for the training dataset and 0.593 for the test dataset. Through the application of LASSO regression and multivariable logistic regression, a screening process was conducted for seven risk factors: D-dimer, blood platelet, hyperlipidemia, blood group, preoperative anticoagulant, spinal cord injury, lower extremity varicosities. Model B demonstrated superior and consistent predictive performance, with ROC AUC values of 0.809 for the training dataset and 0.773 for the test dataset. According to the calibration curves and decision curve analysis, Model B could accurately predict the probability of postoperative DVTp after spine surgery. The nomograms enhanced the interpretability of Model B in charts and graphs. CONCLUSIONS: In summary, we established a logistic regression model for the accurate predicting of postoperative deep vein thrombosis progression in spinal trauma patients, utilizing D-dimer, blood platelet, hyperlipidemia, blood group, preoperative anticoagulant, spinal cord injury, lower extremity varicosities, and age as predictive factors. The proposed model outperformed a logistic regression model based simply on CRS. The proposed model has the potential to aid frontline clinicians and patients in identifying and intervening in postoperative DVTp among traumatic patients undergoing spinal surgery.

Steroidal Saponins from Solanum lyratum Thunb.

Four undescribed steroidal compounds along with twenty known compounds were isolated from n-butanol extracted fraction of the whole plants of Solanum lyratum Thunb (SLNF). Their structures were assigned based on analyses of the extensive spectroscopic data (including MS, 1D/2D NMR, and ECD) or comparisons of the NMR data with those reported. Among the knowns, three compounds were isolated from Solanum plants for the first time, while one compound was isolated from S. lyratum for the first time. In addition, the cytotoxicities of these isolates against human colon SW480 and hepatoma Hep3B cells were evaluated by a MTT assay. And, nine of them and SLNF exhibited significant activities against both SW480 and Hep3B cells, while twelve of them significantly inhibited the activities of SW480 cells. This study allows for the exploitation of chemical markers with potential significance in discrimination of Solanum plants, and uncovers the diverse steroidal constituents from S. lyratum dedicated for its future application in cancer treatment.

[Biochar or Straw Substituting Chemical Fertilizer Increase the Risk of Phosphorus Loss in Subsurface Runoff in Sloping Farmland].

The purple soil slope farmland is an important agricultural land in southwest China but is also one of the main sources of agricultural non-point source pollution in the Three Gorges Reservoir area. Taking reasonable measures to control the loss of soil nutrients is of great significance to the treatment of non-point source pollution in the region. Here, a three-year (2018-2020) field runoff experiment was conducted to monitor and evaluate the phosphorus (P) loss in sloping farmland via surface runoff (i.e., surface flow, 0-20 cm) and subsurface runoff (i.e., subsurface flow, 20-60 cm), with five treatments including no fertilization (CK), conventional fertilization (CF), optimal fertilization (OF), biochar combined with 85% of OF (BF), and straw combined with 85% of OF (SF). The results showed that fertilization application reduced the sediment yields and surface runoff flux but increased the subsurface runoff flux. The total loss flux of phosphate (PO3-4-P), total phosphorus (TP), and particulate phosphorus (PP) in surface flow were the highest in the BF treatment and the lowest in the SF treatment. All fertilization applications increased the P loss fluxes in subsurface flow relative to that in CK. The highest PO3-4-P and TP loss flux in subsurface flow was found in the BF (213.88 g·hm-2 and 694.54 g·hm-2, respectively) treatment, followed by that in the OF and SF treatments. Redundancy analysis (RDA) results showed that surface runoff flux and biochar application were the main factors contributing to increased P loss in surface flow, and subsurface runoff flux was the main factor contributing to increased P loss in subsurface flow. In summary, the SF treatment reduced the amount of sediment yield and surface runoff flux in sloping farmland of purple soil and was the most effective for controlling P loss, whereas the risk of subsurface runoff flux requires further attention.

A correlation study of preoperative lumbar paraspinal muscle quality and L5-S1 lumbar foraminal stenosis degeneration after L4-5 TLIF.

STUDY DESIGN: This was a retrospective study. OBJECTIVES: Adjacent segment degeneration (ASD) is a major complication associated with spinal fusion. The lumbar paraspinal muscle is an essential factor influencing the occurrence of ASD. This study aimed to investigate the effect of preoperative lumbar paraspinal muscle quality on L5-S1 adjacent lumbar foraminal stenosis degeneration (ASLFSD) after L4-5 transforaminal lumbar interbody fusion (TLIF). METHODS: A total of 113 patients diagnosed with lumbar spinal stenosis at L4-5 were treated with TLIF. Lumbar paraspinal muscle measurements were obtained preoperatively and bilaterally from axial T2-weighted MR images. The measurements included the total cross-sectional area of psoas (PS-tCSA), of erector spinae (ES-tCSA), and of multifidus (MF-tCSA); and fatty infiltration of psoas (PS-FI), of erector spinae (ES-FI), and of multifidus (MF-FI). Foraminal measurements, including posterior disc height (PDH), disc-to-facet distance (D-F), foraminal height (FH), and foraminal area (FA), were obtained bilaterally using a computed tomography system. The association between lumbar paraspinal muscle quality and changes in foraminal measurements was also studied. RESULTS: We observed that the FH and FA significantly reduced at 1 year postoperatively at the mean follow-up period of 41.56 ± 8.38 months (range, 43-50 months), and PDH, D-F, FH, and FA all significantly reduced at final follow-up. These changes in foraminal measurements were significantly and negatively correlated with PS-FI, ES-FI, and MF-FI. CONCLUSION: During the clinical follow-up, we found that patients with a higher degree of paraspinal muscle FI were more likely to develop L5-S1 ASLFSD after L4-5 TLIF.

Furfural Derivatives and Phenolic Constituents in Stemona tuberosa Lour.

Chemical investigation on the water-soluble constituents of Stemona tuberosa Lour. resulted in the isolation of a previously undescribed furfural derivative namely (S)-5-((R)-hydroxy(5-(hydroxymethyl)furan-2-yl)methyl)-5-methylfuran-2(5H)-one and twenty-five known compounds from the water decoction of the dried root tubers. Their structures were determined by analysis of the extensive spectroscopic data, including 1D/2D NMR, HR-ESI-MS, and ORD, as well as the ECD simulation and comparison. Most of them were phenolic and among them, four compounds were isolated from Stemona plants for the first time. This study uncovers diverse constituents from water decoction of S. tuberosa dedicated for its quality control and allows for the exploitation of chemical markers with potential significance for discrimination of Stemona plants.

Degradation Profiling of Nardosinone at High Temperature and in Simulated Gastric and Intestinal Fluids.

Nardosinone, a predominant bioactive product from Nardostachys jatamansi DC, is well-known for its promising therapeutic applications, such as being used as a drug on anti-inflammatory, antidepressant, cardioprotective, anti-neuroinflammatory, anti-arrhythmic, anti-periodontitis, etc. However, its stability under varying environmental conditions and its degradation products remain unclear. In this study, four main degradation products, including two previously undescribed compounds [2-deoxokanshone M (64.23%) and 2-deoxokanshone L (1.10%)] and two known compounds [desoxo-narchinol A (2.17%) and isonardosinone (3.44%)], were firstly afforded from the refluxed products of nardosinone in boiling water; their structures were identified using an analysis of the extensive NMR and X-ray diffraction data and the simulation and comparison of electronic circular dichroism spectra. Compared with nardosinone, 2-deoxokanshone M exhibited potent vasodilatory activity without any of the significant anti-neuroinflammatory activity that nardosinone contains. Secondly, UPLC-PDA and UHPLC-DAD/Q-TOF MS analyses on the degradation patterns of nardosinone revealed that nardosinone degraded more easily under high temperatures and in simulated gastric fluid compared with the simulated intestinal fluid. A plausible degradation pathway of nardosinone was finally proposed using nardosinonediol as the initial intermediate and involved multiple chemical reactions, including peroxy ring-opening, keto-enol tautomerization, oxidation, isopropyl cleavage, and pinacol rearrangement. Our findings may supply certain guidance and scientific evidence for the quality control and reasonable application of nardosinone-related products.

Phytochemistry, data mining, pharmacology, toxicology and the analytical methods of Cyperus rotundus L. (Cyperaceae): a comprehensive review.

Cyperus rotundus L. has been widely used in the treatment and prevention of numerous diseases in traditional systems of medicine around the world, such as nervous, gastrointestinal systems diseases and inflammation. In traditional Chinese medicine (TCM), its rhizomes are frequently used to treat liver disease, stomach pain, breast tenderness, dysmenorrheal and menstrual irregularities. The review is conducted to summarize comprehensively the plant's vernacular names, distribution, phytochemistry, pharmacology, toxicology and analytical methods, along with the data mining for TCM prescriptions containing C. rotundus. Herein, 552 compounds isolated or identified from C. rotundus were systematically collated and classified, concerning monoterpenoids, sesquiterpenoids, flavonoids, phenylpropanoids, phenolics and phenolic glycosides, triterpenoids and steroids, diterpenoids, quinonoids, alkaloids, saccharides and others. Their pharmacological effects on the digestive system, nervous system, gynecological diseases, and other bioactivities like antioxidant, anti-inflammatory, anti-cancer, insect repellent, anti-microbial activity, etc. were summarized accordingly. Moreover, except for the data mining on the compatibility of C. rotundus in TCM, the separation, identification and analytical methods of C. rotundus compositions were also systematically summarized, and constituents of the essential oils from different regions were re-analyzed using multivariate statistical analysis. In addition, the toxicological study progresses on C. rotundus revealed the safety property of this herb. This review is designed to serve as a scientific basis and theoretical reference for further exploration into the clinical use and scientific research of C. rotundus. Supplementary Information: The online version contains supplementary materials available at 10.1007/s11101-023-09870-3.

Development of a Dynamic Nomogram for Predicting the Probability of Satisfactory Recovery after 6 Months for Cervical Traumatic Spinal Cord Injury.

OBJECTIVE: Cervical traumatic spinal cord injury (CTSCI) is a seriously disabling disease that severely affects the physical and mental health of patients and imposes a huge economic burden on patients and their families. Accurate identification of the prognosis of CTSCI patients helps clinicians to design individualized treatment plans for patients. For this purpose, a dynamic nomogram was developed to predict the recovery of CTSCI patients after 6 months. METHODS: We retrospectively included 475 patients with CTSCI in our institution between March 2013 and January 2022. The outcome variable of the current study was a satisfactory recovery of patients with CTSCI at 6 months. Univariate analyses and univariate logistic regression analyses were used to assess the factors affecting the prognosis of patients with CTSCI. Subsequently, variables (P < 0.05) were included in the multivariate logistic regression analysis to evaluate these factors further. Eventually, a nomogram model was constructed according to these independent risk factors. The concordance index (C-index) and the calibration curve were utilized to assess the model's predictive ability. The discriminating capacity of the prediction model was measured by the receiver operating characteristic (ROC) area under the curve (AUC). One hundred nine patients were randomly selected from 475 patients to serve as the center's internal validation test cohort. RESULTS: The multivariate logistic regression model further screened out six independent factors that impact the recovery of patients with CTSCI. Including admission to the American Spinal Injury Association Impairment Scale (AIS) grade, the length of high signal in the spinal cord, maximum spinal cord compression (MSCC), spinal segment fractured, admission time, and hormonal therapy within 8 h after injury. A nomogram prediction model was developed based on the six independent factors above. In the training cohort, the AUC of the nomogram that included these predictors was 0.879, while in the test cohort, it was 0.824. The nomogram C-index incorporating these predictors was 0.872 in the training cohort and 0.813 in the test cohort, while the calibration curves for both cohorts also indicated good consistency. Furthermore, this nomogram was converted into a Web-based calculator, which provided individual probabilities of recovery to be generated for individuals with CTSCI after 6 months and displayed in a graphical format. CONCLUSION: The nomogram, including ASIA grade, the length of high signal in the spinal cord, MSCC, spinal segment fractured, admission time, and hormonal therapy within 8 h after injury, is a promising model to predict the probability of content recovery in patients with CTSCI. This nomogram assists clinicians in stratifying patients with CTSCI, enhancing evidence-based decision-making, and individualizing the most appropriate treatment.

Construction and verification of a nomogram predicting the risk of preoperative deep vein thrombosis progression after elective spine surgery.

OBJECTIVE: This study aimed to construct and verify a useful nomogram that predicts the risk of preoperative deep vein thrombosis (DVT) progression after elective spine surgery. METHODS: Data of patients were collected from 366 patients with preoperative DVT who underwent elective spine surgery at our hospital between July 2017 and May 2022. The least absolute shrinkage and selection operator method combined with multivariable logistic regression analysis were applied to select features for the preoperative DVT progression risk model. The model's capability was evaluated using the concordance index (C-index), calibration curve, and receiver operating characteristic (ROC) curve. The decision curve and bootstrapping were used to analyze the clinical value of the nomogram. RESULT: A total of 366 DVT patients were enrolled in this study. Preoperative DVT progression after elective spine surgery was 24.04% (88 cases). Among these patients, 86 patients had thrombosis extending into a proximal vein or appearing in a different branch of the vein, either ipsilateral or contralateral, and two had a symptomatic pulmonary embolism. D-dimer, lower extremity varicosities, hyperlipidemia, lower limb paralysis, and operation time were among the predictors in the nomogram. Furthermore, the C-index of the prediction nomogram was 0.805 (95％ CI: 0.754-0.856), with an interval bootstrapping validation of 0.786 and an area under the ROC curve value of 0.800. According to the calibration curves and decision curve analysis, the nomogram could accurately predict the probability of preoperative DVT progression after elective spine surgery. CONCLUSION: The advantages of the nomogram included the unique discrimination capability, clinical utility, and predictive accuracy, which was beneficial for clinicians to distinguish high-risk groups of DVT progression after elective spine surgery and formulate relevant prevention measures.

Association between visceral fat and osteoporotic vertebral compression refractures.

OBJECTIVES: The aims of this study were to examine the association between osteoporotic vertebral compression refractures (OVCRFs) and visceral fat and to identify other risk factors for OVCRFs. METHODS: We included 311 patients with OVCRs who underwent percutaneous kyphoplasties (PKPs) at our hospital between May 2016 and December 2017. The visceral fat area (VFA) at the plane of the third lumbar vertebra was assessed using preoperative computed tomography (CT) scans. The patients were divided into two groups: OVCRFs and non-OVCRFs. The perioperative variables were compared between the two groups. Univariate and multivariate analyses were used to determine independent risk factors for OVCRFs. Correlation analysis was performed to investigate the association between bone mineral density (BMD) and visceral fat. RESULTS: During the 1-y follow-up, 311 patients were included in the analysis. OVCRFs occurred in 69 patients (22.19%). High VFA was present in 163 patients (52.41%), including 52 OVCRFs and 111 non-OVCRF patients. In all the patients, high VFA (P < 0.001), older age (P = 0.022), female sex (P = 0.020), lower body mass index (BMI; P = 0.028), lower albumin levels (P < 0.001), lower hemoglobin levels (P = 0.045), lower BMD (P < 0.001), lower L3 skeletal muscle index (L3 SMI; P < 0.001), lower subcutaneous fat area (SFA; P = 0.003), higher VFA/SFA ratio (V/S ratio; P < 0.001), higher visceral fat area/muscle area (V/M) ratio (P < 0.001), and higher visceral fat index (VFI; P = 0.001) were associated with OVCRFs. Multivariate analysis revealed that patients of female sex (P < 0.001) and high VFA (P < 0.001) were independent risk predictors for OVCRFs. Higher BMD (P = 0.014) was a protective predictor of OVCRFs. Among all the overweight and obese patients (BMI ≥24 kg/m2), high VFA(P = 0.002), female sex (P = 0.044), lower albumin levels (P = 0.003), lower hemoglobin levels (P = 0.010), lower vitamin D levels (P = 0.037), lower BMD (P < 0.001), lower L3 SMI (P = 0.015), higher V/S ratios (P = 0.003), higher V/M ratios (P < 0.001), and higher VFIs (P = 0.005) were associated with OVCRFs. Multivariate analysis revealed that higher VFAs (P = 0.004) remained an independent predictor of OVCRFs in overweight and obese patients. Higher BMD (P = 0.011) was a protective predictor of OVCRFs. In the correlation analysis, a negative correlation was observed between the BMD and both the visceral fat area and V/M ratio. CONCLUSIONS: High VFA is a highly independent risk factor for OVCRFs. Other factors affecting OVCRFs include belonging to the female sex and low BMD. In overweight and obese patients, high VFA and low BMD are independent risk factors for OVCRFs.

[Effects of Biochar and Straw Return on Soil Aggregate and Organic Carbon on Purple Soil Dry Slope Land].

The aim of the study was to understand the impact of biochar and straw return on soil aggregates and organic carbon for soil improvement of the newly cultivated purple soil dry slope land in the Three Gorges Reservoir area. In this study, a field test was used to set five treatment pairs with regards to soil aggregate composition and organic carbon distribution:no fertilization(CK), conventional fertilization(NPK), optimized fertilization(GNPK), chemical fertilizer reduction combined with straw(RSD), and chemical fertilizer reduction combined with biochar(BC). The results showed that fertilization can improve the level of soil fertility, especially with the RSD and BC treatments. The soil aggregates of each fertilization treatment were<0.25 mm in size. Compared with the CK, each treatment significantly increased the aggregate content of 0.5-5 mm particles, and the values of MWD, GMD, and R0.25. Further, the treatments significantly reduced the value of D and PAD0.25(P<0.05), and each fertilization treatment significantly increased the soil organic carbon content, of which BC(6.73 g·kg-1) and RSD(5.45 g·kg-1) were significantly better than NPK(5.05 g·kg-1) and GNPK(3.63 g·kg-1). The<0.25 mm aggregates had the highest contribution rate of organic carbon(34.92%-59.49%), while the>5 mm aggregates had the lowest contribution rate of organic carbon(1.55%-6.01%). The BC treatment significantly increased the organic carbon contribution rate of 5-2 mm and 2-1 mm agglomerates(P<0.05), while the contribution rate of NPK, RSD, and GNPK was the most significant for 0.5-0.25 mm(P<0.05). Each fertilization treatment increased the yield of rapeseed and corn, with large inter-annual differences, but the overall difference between treatments was not significant. The stability of soil aggregates and crop yields showed an upward trend with the increase of soil organic carbon. Biochar and straw returning to the field may promote the formation of large and medium aggregates in soil, effectively improve the stability of aggregates, increase organic carbon content, and promote crop yields. It is therefore an effective measure to improve the soil structure of purple soil and improve soil quality.