Detection of wheat saccharification power and protein content using stacked models integrated with hyperspectral imaging.

BACKGROUND: Wheat is one of the key ingredients used to make Chinese liquor, and its saccharification power and protein content directly affect the quality of the liquor. In pursuit of a non-destructive assessment of wheat components and the optimization of raw material proportions in liquor, this study introduces a precise predictive model that integrates hyperspectral imaging (HSI) with stacked ensemble learning (SEL). RESULTS: This study extracted hyperspectral information from 14 different varieties of wheat and employed various algorithms for preprocessing. It was observed that multiplicative scatter correction (MSC) emerged as the most effective spectral preprocessing method. The feature wavelengths were extracted from the preprocessed spectral data using three different feature extraction methods. Then, single models (support vector machine (SVM), backpropagation neural network (BPNN), random forest (RF), and gradient boosting tree (XGBoost)) and a SEL model were developed to compare the prediction accuracies of the SEL model and the single models based on the full-band spectral data and the characteristic wavelengths. The findings indicate that the MSC-competitive adaptive reweighted sampling-SEL model demonstrated the highest prediction accuracy, with Rp 2 (test set-determined coefficient) values of 0.9308 and 0.9939 for predicting the saccharification power and protein content and root mean square error of the test set values of 0.0081 U and 0.0116 g kg-1, respectively. CONCLUSION: The predictive model established in this study, integrating HSI and SEL models, accurately detected wheat saccharification power and protein content. This validation underscores the practical potential of the SEL model and holds significant importance for non-destructive component analysis of raw materials used in liquor. © 2024 Society of Chemical Industry.

First principles study of structural and electron properties in scorodite: the bulk and surface.

Scorodite (FeAsO4·2H2O) is an ideal material for the fixation of arsenic that has attracted considerable research interest in recent decades. However, the position of the H atom in the scorodite crystal structure, water molecular configuration, surface morphology, and chemical state of the surface atoms have not been reported. In this work, density functional theory (DFT) is used to optimize the scorodite crystal structure, and the atomic bonding is analyzed. At the same time, a surface model is constructed to calculate the configuration and electronic structure of the surface atoms for different coordination groups. The results show that the tetrahedral [AsO4] and octahedral [FeO4(2H2O)] groups in the scorodite crystal structure have good stability(geometry configuration), and the covalent bond strength between the As atom and the bridged oxygen atom (Ob) is greater than that between the Ob atom and the Fe atom. The water molecules in the crystal structure do not seriously deform and ionize. The configuration of the water molecules remains stable through electrostatic interactions (Ow-Fe) and hydrogen bonding (H-Ob). The Fe atoms on the surface of scorodite can coordinate with OH and H2O, while the As atoms can only form a stable coordination with OH. When an Fe atom on the surface coordinates with two H2O atoms, the Fe atom will shrink to the inside of the bulk. With the increase in the hydroxylation number of the Fe atom, the bonding strength between the Fe atom and the Ob atom decreases. Different surface configurations do not affect the stability(geometry configuration) of the [AsO4] structure. In addition, the surface water molecular layer has a very weak effect on the surface coordination configuration. By contrast, in the surface configuration of the (W + OH) structure, the change in the surface atomic layer spacing is the smallest.

Atomic reconstruction and oxygen adsorption behavior of the pyrite (100) surface: a DFT study.

The analysis of the surface chemical behavior of pyrite is highly crucial in the fields of environmental conservation, metal extraction, and flotation separation. In this paper, the mechanism of atomic reconstruction on the pyrite surface and the adsorption behavior of O2 on a reconstructed surface are calculated by density functional theory (DFT). Different reconstruction surfaces were constructed by deleting S and Fe atoms on the (100) surface of pyrite. In addition, the geometric configuration, formation energy, binding energy, cohesion energy, and surface electronic properties of the reconstruction surface were calculated. The adsorption energies and geometric configurations of O2 on different reconstructed surfaces were also determined. The results show that under Fe-poor conditions, the charge of Fe atoms increases, and S atoms form Sn on the reconstructed surface. The binding energy between the Sn and the substrate (ideal surface) is lower, which is similar to the Sn adsorption on the substrate surface with the Fe atom as the site. Sn has high cohesive energy and is resistant to being attacked by oxidants, which leads to structural collapse, and a low affinity for O2. Under S-poor conditions, the -[Fe-S]n- plane structure formed on the reconstructed surface. The -[Fe-S]n- structure stably bonds to the substrate by an Fe-S bond, and exhibits strong binding energy. However, the -[Fe-S]n- structure has low cohesive energy and exhibits thermodynamic instability. In contrast, O2 shows a strong affinity for the -[Fe-S]n- structure, indicating that the deficiency of the S atom promotes the surface oxidation reaction. The mechanism of atomic reconstruction on the surface of pyrite is of utmost importance for understanding its surface chemical behavior.

Rapid nondestructive detecting of sorghum varieties based on hyperspectral imaging and convolutional neural network.

BACKGROUND: The purity of sorghum varieties is an important indicator of the quality of raw materials used in the distillation of liquors. Different varieties of sorghum may be mixed during the acquisition process, which will affect the flavor and quality of liquor. To facilitate the rapid identification of sorghum varieties, this study proposes a sorghum variety identification model using hyperspectral imaging (HSI) technology combined with convolutional neural network (AlexNet). RESULTS: First, the watershed algorithm, which was modified with the extended-maxim transform, was used to segment the hyperspectral images of a single sorghum grain. The isolated forest algorithm was used to eliminate abnormal spectral data from the complete spectral data. Secondly, the AlexNet model of sorghum variety identification was established based on the two-dimensional gray image data of sorghum grain in group 1. The effects of different preprocessing methods and different convolution kernel sizes on the performance of the AlexNet model were discussed. The eigenvalues of the last layer of the AlexNet model were visualized using the t-distributed random neighborhood embedding method, which is used to evaluate the separability of features extracted by the AlexNet model. The performance differences between the optimal AlexNet model and traditional machine learning models for sorghum variety identification were compared. Finally, the varieties of sorghum grains in groups 2 and 3 were identified based on the optimal AlexNet model, and the average accuracy values of the test set reached 95.62% and 95.91% respectively. CONCLUSION: The results in this study demonstrated that HSI combined with the AlexNet model could provide a feasible technical approach for the detection of sorghum varieties. © 2022 Society of Chemical Industry.

Accuracy of the trough position in expansive open-door cervical laminoplasty using computer navigation techniques: a single-centre retrospective study.

PURPOSE: This study aims to assess whether computer navigation can improve the accuracy of the trough position and clinical outcomes of expansive open-door cervical laminoplasty (EOLP). METHODS: We reviewed a single centre of 28 conventional EOLP and 24 computer navigation EOLP cases. The conventional group had 102 laminae while the navigation group had 88. The distance from the medial cortex to the pedicle on the open-door side (OD) and hinge side (HD) was measured. Furthermore, the area of the spinal canal corresponding to each lamina before and after the surgical procedure was also measured. We then compared the differences in radiographic parameters and clinical outcomes between the two groups. RESULTS: OD and HD were smaller in the navigation group compared to the conventional group, and the enlarged area of the spinal canal was larger in the navigation group than in the conventional group. The Japanese Orthopaedic Association (JOA) scores one year after the surgical procedure improved in both groups compared to the pre-operative period, and the JOA recovery rate was higher in the navigation group. The incidence of hinge fracture was lower in the navigation group, and the incidence of C5 palsy and axial pain was not statistically different between the two groups. CONCLUSION: The use of computer navigation techniques has the potential to significantly improve the accuracy of EOLP compared to conventional procedures. It has been shown to more fully expand the spinal canal and contribute to clinical efficacy.

Effects of emergency cervical cerclage on pregnancy outcome: a retrospective study of 158 cases.

The aim of this study was to evaluate the effectiveness and safety of emergency cervical cerclage in women with advanced cervical dilatation and bulging of fetal membranes. The study included 158 women who underwent emergency cervical cerclage because of cervix dilatation and protruding membranes in mid-trimester at Sun Yat-sen Memorial Hospital of Sun Yat-sen University. Pregnancy outcomes and pregnancy outcome related to clinical features were analyzed retrospectively. Analysis revealed that the placement of emergency cerclage led to the delivery of live infants with a success rate of 82.28%. The mean interval between cerclage and delivery was 52.16.±26.62 days, with a mean gestation at delivery of 30.3±4.7 weeks and a mean birth weight of 1934.69±570.37 g. No severe maternal complications such as maternal death, hematosepsis, and hysterorrhexis occurred after the operation. Two women (1.25%) had laceration of the cervix, 1 woman (0.61%) suffered pulmonary edema, and 2 women (1.25%) developed deep vein thrombosis (DVT). There were significant correlations between the pregnancy outcome and risk factors, including any presenting symptoms, cervical dilatation, postoperative white blood cell count, and C-reactive protein (CRP) value. No significant difference was found in women with good vs. poor outcome in terms of maternal age and obstetric histories. Emergency cervical cerclage is effective in prolonging pregnancy and improving neonatal outcome in women with cervical incompetence. It should be considered a viable option for women with a dilated cervix in mid-trimester.

Mechanistic studies of adsorption and ion exchange of Si(OH)4 molecules on the surface of scorodites.

Scorodites are commonly used for arsenic immobilization, and it is also the main component of arsenic bearing tailings. Alkali-activated geopolymers are commonly used to landfill arsenic-bearing minerals. However, there no previous studies have explored the interaction between geopolymer molecules and the surface of scorodite. In this paper, Si(OH)4 as a monomer molecule of geopolymer, the mechanism of adsorption and 'ion exchange' between Si(OH)4 molecule and the surface of scorodite during alkali-activation is studied. Results show that the Fe-terminated scorodite (010) surface has high stability. Si(OH)4 are more easily adsorbed on the hollow site of an Fe-terminated scorodite (010) surface, which is described as chemisorption. Compared with Si(OH)4, NaOH is easier to adsorb on an Fe-terminated scorodite (010) surface. The co-adsorption of NaOH and Si(OH)4 on the Fe-terminated scorodite (010) surface was studied, and also belongs to chemical adsorption. When the hydroxyl binds to the As atom, the adsorbed Si(OH)4 is more likely to undergo an 'ion exchange' reaction with the surface, and the reaction is barrierless. The intermediate As(OH)4 produced by the 'ion exchange' reaction can be deprotonated to form an arsenate molecule, which can occur spontaneously. This work reveals that the interaction mechanism of geopolymer molecules on surface of scorodite.

Investigation of liquor microstructure (ethanol-water clusters): Molecular dynamics simulation and density functional theory.

Ethanol and water are the primary components of liquor. In this study, molecular dynamics (MD) simulations and density functional theory (DFT) were used to model ethanol-water clusters and infer possible structures of ethanol-water solutions. Nuclear magnetic resonance (NMR) and density of states analysis were employed to confirm the existence of clusters and further describe their properties. By comparing binding energies and calculating coordination numbers, we found that the ethanol-water solution with a molecular ratio of 1:2 forms three stable clusters. Under ideal conditions, the cluster ratio is approximately 1:1:6. Generally, the clusters undergo continuous splitting and recombination.

Rapid determination of starch and alcohol contents in fermented grains by hyperspectral imaging combined with data fusion techniques.

Starch and alcohol serve as pivotal indicators in assessing the quality of lees fermentation. In this paper, two hyperspectral imaging (HSI) techniques (visible-near-infrared (Vis-NIR) and NIR) were utilized to acquire separate HSI data, which were then fused and analyzed toforecast the starch and alcohol contents during the fermentation of lees. Five preprocessing methods were first used to preprocess the Vis-NIR, NIR, and the fused Vis-NIR and NIR data, after which partial least squares regression models were established to determine the best preprocessing method. Following, competitive adaptive reweighted sampling, successive projection algorithm, and principal component analysis algorithms were used to extract the characteristic wavelengths to accurately predict the starch and alcohol levels. Finally, support vector machine (SVM)-AdaBoost and XGBoost models were built based on the low-level fusion (LLF) and intermediate-level fusion (ILF) of single Vis-NIR and NIR as well as the fused data. The results showed that the SVM-AdaBoost model built using the LLF data afterpreprocessing by standard normalized variable was most accurate for predicting the starch content, with an R P 2 $\ R_P^2$ of 0.9976 and a root mean square error of prediction (RMSEP) of 0.0992. The XGBoost model built using ILF data was most accurate for predicting the alcohol content, with an R P 2 $R_P^2$ of 0.9969 and an RMSEP of 0.0605. In conclusion, the analysis of fused data from distinct HSI technologies facilitates rapid and precise determination of the starch and alcohol contents in fermented grains.

Multicomponent hyperspectral grade evaluation of ilmenite using spectral-spatial joint features.

Obtaining a comprehensive understanding of ore grade information is of significant importance for evaluating the value of ore. However, the real-time detection of multicomponent grade needs more effective online methods. This study proposes a novel approach utilizing hyperspectral imaging (HSI) to evaluate the grade information of nine major ilmenite components by integrating spectral and spatial data. Four multivariate input-output models were developed to mitigate variable interference to predict each component's grade. The results demonstrated that the backpropagation neural network (BPNN) model built from iPLS-VCPA-IRIV feature selection spectral data worked best (RP2 = 0.9935, RMSEP = 0.1364, RPD = 12.8986, and RPIQ = 21.4871, with a computational time of approximately 0.8 s). Furthermore, applying the best optimal combination algorithm for multicomponent grade inversion yielded highly accurate results, in which 97% of the component inversion residuals were less than 1. This investigation affirms that HSI enables rapid and accurate prediction and inversion of the multicomponent grade of ilmenite, thereby presenting a promising alternative to online analysis in the mineral field.

Chromosome-level genome and multi-omics analyses provide insights into the geo-herbalism properties of Alpinia oxyphylla.

Introduction: Alpinia oxyphylla Miquel (A. oxyphylla), one of the "Four Famous South Medicines" in China, is an essential understory cash crop that is planted widely in the Hainan, Guangdong, Guangxi, and Fujian provinces. Particularly, A. oxyphylla from Hainan province is highly valued as the best national product for geo-herbalism and is an important indicator of traditional Chinese medicine efficacy. However, the molecular mechanism underlying the formation of its quality remains unspecified. Methods: To this end, we employed a multi-omics approach to investigate the authentic quality formation of A. oxyphylla. Results: In this study, we present a high-quality chromosome-level genome assembly of A. oxyphylla, with contig N50 of 76.96 Mb and a size of approximately 2.08Gb. A total of 38,178 genes were annotated, and the long terminal repeats were found to have a high frequency of 61.70%. Phylogenetic analysis demonstrated a recent whole-genome duplication event (WGD), which occurred before A. oxyphylla's divergence from W. villosa (~14 Mya) and is shared by other species from the Zingiberaceae family (Ks, ~0.3; 4DTv, ~0.125). Further, 17 regions from four provinces were comprehensively assessed for their metabolite content, and the quality of these four regions varied significantly. Finally, genomic, metabolic, and transcriptomic analyses undertaken on these regions revealed that the content of nootkatone in Hainan was significantly different from that in other provinces. Discussion: Overall, our findings provide novel insights into germplasm conservation, geo-herbalism evaluation, and functional genomic research for the medicinal plant A. oxyphylla.

Nondestructive visualization and quantification of total acid and reducing sugar contents in fermented grains by combining spectral and color data through hyperspectral imaging.

Total acid content (TAC) and reducing sugar content (RSC) are important evaluation indicators for the quality of fermented grains. In this study, the TAC and RSC of fermented grains were quantified using hyperspectral imaging (HSI). Two combined algorithms were used to extract the characteristic wavelengths of TAC and RSC. Nine color features of fermented grains were extracted based on H, S and V color channels. Multivariate analytical models were developed to predict TAC and RSC using full wavelengths, characteristic wavelengths, color features and fused data, respectively. The CF model established based on characteristic wavelengths extracted by CARS-SPA showed the best results in predicting TAC. Meanwhile, the PSO-SVR model built using fused data was the best model for predicting RSC. The visualization of the TAC and RSC was achieved using the optimal models. These results show that HSI can achieve non-destructive detection and visualization of TAC and RSC in fermented grains.

Rapid and nondestructive determination of sorghum purity combined with deep forest and near-infrared hyperspectral imaging.

This study combined hyperspectral imaging (HSI) and deep forest (DF) to develop a reliable model for conducting a rapid and nondestructive determination of sorghum purity. Isolated forest (IF) algorithm and principal component analysis (PCA) were used to remove the abnormal data of sorghum grains. Competitive adaptive reweighted sampling (CARS) algorithm and successive projections algorithm (SPA) were combined and used to extract the characteristic wavelengths. Gray-level co-occurrence matrix (GLCM) was used to extract the textural features. DF models were established based on the different types of data. Specifically, the DF models established using the characteristic spectra produced the best recognition results: the average correct recognition rate (CRR) of the models was greater than 91%. In addition, the average CRR of validation set Ⅰ was 88.89%. These results show that a combination of HSI and DF could be used for the rapid and nondestructive determination of sorghum purity.

Rapid and nondestructive prediction of amylose and amylopectin contents in sorghum based on hyperspectral imaging.

The contents of amylose and amylopectin in sorghum directly affects the quality and yield of liquor. Hyperspectral imaging (HSI) is an emerging technology widely applied in the content analysis of food ingredients. In this study, the effects of different preprocessing methods on visible-light and near-infrared spectral data were analyzed, and the prediction accuracies of these spectral data were compared. Principal components analysis (PCA) and successive projections algorithm (SPA) were combined to extract the characteristic wavelengths. Using both the full and characteristic wavelengths, partial least square regression (PLSR) and cascade forest (CF) models were developed to predict the contents of amylose and amylopectin in different varieties of sorghum. The average RPD values of the CF models established by the characteristic wavelengths were 4.7622 and 5.5889, respectively. These results corroborated the utility of HSI in achieving the rapid and nondestructive prediction of amylose and amylopectin contents in different varieties of sorghum.

Rapid and nondestructive detection of sorghum adulteration using optimization algorithms and hyperspectral imaging.

This paper proposes a sorghum adulteration detection model using hyperspectral imaging technology (HSI), image processing technology, and multivariate analysis technology. The model used a watershed algorithm to extract hyperspectral data from sorghum grains. Principal component analysis (PCA) and clustering analysis (CA) were used to remove abnormal samples of sorghum. Partial least squares discriminant analysis (PLS-DA) was used to identify the variety of sample, and a sorghum distribution map and adulteration ratios were obtained by marking varieties with different colors. This paper presents, for the first time, HSI use for identification of adulteration in sorghum using PCA and CA. Accuracy of the model identification for the validation set reached 96%, and for the adulterated samples reached 91%, and comprehensive accuracy of the model could reach more than 90%. These results show that the model can rapidly and nondestructively detect sorghum adulteration.

Rapid determination of pit mud moisture content using hyperspectral imaging.

Lack of moisture can lead to the aging of pit mud, excessive moisture will make it difficult to maintain its shape or even collapse. Therefore, a rapid and nondestructive detection technology for moisture in pit mud using hyperspectral imaging was firstly investigated. Modeling efficiency of various processing was compared in visible (400-1,000 nm) and near-infrared (900-1,700 nm) regions, and the optimal model was SNV-SPA-SVM in near-infrared spectroscopy; the R pre 2 and RMSEP of model were .9953 and 0.0029, respectively. Furthermore, the distribution map showed that the moisture in the new cellar was generally lower than that of old, and the moisture distribution of the old pit mud was more even. Moreover, the moisture content of different layers in the same cellar increased from top to bottom. This work provides strong technical support for liquor brewing enterprises to effectively implement online monitoring of pit mud changes and open a new era for the application of hyperspectral imaging technology in the field of liquor solid-state fermentation.

Application of hyperspectral technology in detection of agricultural products and food: A Review.

Food is the foundation of human survival. With the development and progress of society, people increasingly focus on the problems of food quality and safety, which is closely related to human's health. Thus, the whole industrial chain from farmland to dining table need to be strictly controlled. Traditional detection methods are time-consuming, laborious, and destructive. In recent years, hyperspectral technology has been more and more applied to food safety and quality detection, because the technology can achieve rapid and nondestructive detection of food, and the requirement to experimental condition is low; operability is strong. In this paper, hyperspectral imaging technology was briefly introduced, and its application in agricultural products and food detection in recent years was systematically summarized, and the key points in the research process were deeply discussed. This work lays a solid foundation for the peers to the following in-depth research and application of this technology.

Effect of Alpina oxyphylla extract on streptozotocin-induced kidney injure via regulating TGF-ß1 and MyD88.

BACKGROUND: Abnormal renal metabolism is closely related to the development of chronic kidney disease. It is well known that renal inflammation plays an important role in the occurrence and development of tubulointerstitial damage in the renal tubules. The purpose of the experiment was to observe the bioactivity of Alpina oxyphylla extract (AOE) on renal injury in diabetic nephropathy (DN) rats induced by streptozotocin (STZ). METHODS: Thirty male Wistar rats were randomly divided into five group (n = 6): (1) intact control (non-diabetic, ND); (2) intact diabetic (STZ), (3) diabetic rats treated with gliclazide 5 mg/kg (STZ-gli), (4) diabetic rats treated with AOE 400 mg/kg (AOE 400), (5) diabetic rats treated with AOE 800 mg/kg (AOE 800). The diabetic nephropathy rat model was established by single intraperitoneal injected 50 mg/kg STZ. Fasting blood glucose (FBG) and body weight was observed at 1、3、6 weeks. After 6 weeks, the renal function parameters of five groups and 24 h urinary protein were detected. Expression of transforming growth factor-beta1 (TGF-ß1) and myeloid differentiation factor 88 (MyD88) were assessed by Western Blot. RESULTS: The STZ group showed hyperglycemia, proteinuria, renal function damage, and the levels of 24 h urinary protein, fasting blood glucose (FBG), blood urea nitrogen (BUN), serum creatinine (Scr), triglyceride (TG), high-density lipoprotein cholesterol (HDL-C) and interleukin-6 (IL-6) in the STZ group increased significantly compared with the ND group. The expression of TGF-ß1 in STZ group was increase (p < 0.01), and the expression of MyD88 was significantly lower than in ND group (p < 0.05). The treatment of DN rats with AOE attenuated DN-associated in the serum biochemical index and the expression of TGF-ß1. CONCLUSIONS: AOE can effectively protect kidney tissues of diabetic nephropathy, and probably through regulating level of TGF-ß1/MyD88.

[Effect of bloodletting acupuncture at twelve jing-well points of hand on microcirculatory disturbance in mice with traumatic brain injury].

OBJECTIVE: To observe the effect of bloodletting acupuncture at twelve jing-well points of hand on microcirculatory disturbance in mice with traumatic brain injury (TBI), and to explore the protective effect of bloodletting therapy on TBI. METHODS: Sixty clean adult male C57BL/6J mice were randomly divided into a sham-operation group, a model group and a treatment group, 20 mice in each group. The TBI model was established by using electronic controlled cerebral cortex impact instrument in the model group and the treatment group. The mice in the treatment group were treated with bloodletting acupuncture at bilateral "Shaoshang" (LU 11), "Shangyang" (LI 1), "Zhongchong" (PC 9), "Guanchong" (TE 1), "Shaochong" (HT 9) and "Shaoze" (SI 1) immediately after trauma. The mice in the sham-operation group only opened the bone window but did not receive the strike. The regional cerebral blood flow (rCBF) was monitored by laser speckle contrast analysis (LASCA) using a PeriCam PSI System before trauma, immediately after trauma and 1, 2, 12, 24, 48, 72 h after trauma. The brain water content was measured by wet-dry weight method 24 h after trauma. The severity of functional impairment at 2, 12, 24, 48 and 72 h after trauma was evaluated by modified neurological scale scores (mNSS). RESULTS: ① 2 h after trauma, the mNSS in the model group and treatment group were >7 points, suggesting the successful establishment of model; compared with the sham-operation group, the mNSS was increased significantly from 12 to 72 h after trauma in the model group ( all P<0.01), but the mNSS in the treatment group was significantly lower than that in the model group from 2 to 24 h after trauma (P<0.01, P<0.05). ② Compared with the sham-operation group, rCBF in the model group was decreased significantly immediately after trauma (P<0.01), and the rCBF in the model group was lower than that in the sham-operation group from 1 to 72 h after trauma ( all P<0.01); rCBF in the treatment group began to rise and was significantly higher than that in the model group 1-2 h after trauma (P<0.01); 12-48 h after trauma, the increasing of rCBF in the two groups tended to be gentle until 72 h after injury, and rCBF in the model group was decreased while that in the treatment group continued to rise and was higher than that in the model group (P<0.01). ③ 24 h after trauma, the brain water content in the model group was significantly higher than that in the sham-operation group (P<0.01), and brain water content in the treatment group was significantly lower than that in the model group (P<0.01). CONCLUSION: The bloodletting acupuncture at twelve jing-well points of hand could improve microcirculation disturbance, increase microcirculation perfusion, alleviate secondary brain edema and promote the recovery of nerve function in mice with TBI.

Modified Lumbosacral Angle and Modified Pelvic Incidence as New Parameters for Management of Pediatric High-grade Spondylolisthesis.

STUDY DESIGN: Retrospective clinical study. OBJECTIVE: We aimed to introduce new parameters that can better describe the pelvic morphology and lumbosacral segmental deformity in children with high-grade spondylolisthesis of the L5 vertebra: modified pelvic incidence (mPI) and modified lumbosacral angle (mLSA). Also, we aimed to establish the mLSA as a convenient, reliable measurement method and criteria to evaluate the reduction of L5 vertebral slippage. SUMMARY OF BACKGROUND DATA: Numerous parameters and methods exist to evaluate segmental deformity and reduction of L5 vertebral slippage, but no definitive standard for accurately and conveniently describing lumbosacral kyphosis and degree of reduction exists. METHODS: A total of 24 children with high-grade spondylolisthesis (S group) and 152 children without spondylolisthesis (non-S group) underwent standard lateral radiography of the spine in our hospital between June 2009 and June 2014. We compared mPI and mLSA between the S and non-S groups. The agreement and repeatability of mPI and mLSA were also assessed. Preoperative and postoperative Japanese Orthopaedic Association (JOA) and Scoliosis Research Society (SRS)-22 scores were compared to assess clinical outcomes in the S group. The correlations between modified parameter applications and clinical outcomes were also assessed. RESULTS: While mPI did not differ between groups, mLSA differed significantly. In the non-S group, mLSA was lordotic (25.51±6.41 degrees). In the S group, mLSA was kyphotic (25.85±5.17 degrees) before surgery and lordotic (20.74±7.04 degrees) postoperatively. The agreement and repeatability of mPI and mLSA were good, and clinical outcomes of the S group were satisfactory. Positive correlations were found between modified parameter applications and the improvement rates of JOA scores. CONCLUSIONS: mPI and mLSA can better describe the pelvic morphology and local deformity of pediatric high-grade L5 spondylolisthesis, and mLSA can serve as a useful index for correcting lumbosacral kyphosis, rebalancing the sagittal spinal profile and predicting clinical outcomes.