Analysis of Degenerative and Isthmic Lumbar Spondylolisthesis from the Difference of Pelvic Parameters and the Degree of Degeneration through Imaging Data

Background: In previous studies, many imaging analyses have been conducted to explore the changes in the intervertebral disc degeneration (DD), facet joint osteoarthritis (FJOA), L4 inclination angle (L4IA), pelvis-related parameters, lumbar lordosis (LL), and paravertebral muscle (PVM) in the occurrence and development of degenerative spinal diseases via measuring the X-ray, CT, and MRI data of clinical patients. However, few studies have quantitatively investigated the pelvic parameters and the degree of spine degeneration in patients with degenerative lumbar spondylolisthesis (DLS) and isthmic lumbar spondylolisthesis (ILS). This study discusses the changes in the imaging parameters of DLS, ILS, and a control group; explores the correlation between different measurement parameters; and discusses their risk factors. Methods: We evaluated 164 patients with single L4-L5 grade 1 level degenerative lumbar spondylolisthesis (DLS group), 161 patients with single L4-L5 grade 1 level isthmic lumbar spondylolisthesis (ILS group), and 164 patients with non-specific back pain (control group). The grades of DD and FJOA as well as the percentage of the fat infiltration area (%FIA) of multifidus muscle (MM) at the L4-L5 level were measured via CT and MRI. Lumbar lordosis (LL), pelvic incidence (PI), pelvic tilt (PT), the L4 inclination angle (L4IA), and sacral slope (SS) were measured via X-ray film, and the differences among the DLS group, ILS group, and control group were analyzed. Furthermore, the risk factors related to the incidences of the DLS and ILS groups were discussed. Results: First, the pelvis-related parameters of DLS and ILS patients were 51.91 ± 12.23 and 53.28 ± 11.12, respectively, while those of the control group were 40.13 ± 8.72 (p1 p2 p p p < 0.05). Finally, logistic regression suggests that the L4IA, FJOA, and PT may be risk factors for the occurrence of DLS, and the occurrence of ILS is correlated with the L4IA, FJOA, DD, PT, and LL. Conclusions: Compared with the control group, there are changes in pelvic parameters, the L4IA, LL, DD, FJOA, and PVM in DLS and ILS patients, and the degree is different. The parameters within the same group are related to each other, and DLS and ILS have different risk factors. The mechanical stability of the spine is affected by the parameter and angle changes, which may be of great significance for explaining the cause of spondylolisthesis, evaluating the health of the lumbar spine, and guiding the lifestyles of patients

Spectrum-Effect Relationships between Fingerprints of Caulophyllum robustum Maxim and Inhabited Pro-Inflammation Cytokine Effects

Caulophyllum robustum Maxim (CRM) is a Chinese folk medicine with significant effect on treatment of rheumatoid arthritis (RA). This study was designed to explore the spectrum-effect relationships between high-performance liquid chromatography (HPLC) fingerprints and the anti-inflammatory effects of CRM. Seventeen common peaks were detected by fingerprint similarity evaluation software. Among them, 15 peaks were identified by Liquid Chromatography-Mass Spectrometry (LC-MS). Pharmacodynamics experiments were conducted in collagen-induced arthritis (CIA) mice to obtain the anti-inflammatory effects of different batches of CRM with four pro-inflammation cytokines (TNF-α, IL-β, IL-6, and IL-17) as indicators. These cytokines were suppressed at different levels according to the different batches of CRM treatment. The spectrum-effect relationships between chemical fingerprints and the pro-inflammation effects of CRM were established by multiple linear regression (MLR) and gray relational analysis (GRA). The spectrum-effect relationships revealed that the alkaloids (N-methylcytisine, magnoflorine), saponins (leiyemudanoside C, leiyemudanoside D, leiyemudanoside G, leiyemudanoside B, cauloside H, leonticin D, cauloside G, cauloside D, cauloside B, cauloside C, and cauloside A), sapogenins (oleanolic acid), β-sitosterols, and unknown compounds (X3, X17) together showed anti-inflammatory efficacy. The results also showed that the correlation between saponins and inflammatory factors was significantly closer than that of alkaloids, and saponins linked with less sugar may have higher inhibition effect on pro-inflammatory cytokines in CIA mice. This work provided a general model of the combination of HPLC and anti-inflammatory effects to study the spectrum-effect relationships of CRM, which can be used to discover the active substance and to control the quality of this treatment

Expression of Pinellia pedatisecta Lectin Gene in Transgenic Wheat Enhances Resistance to Wheat Aphids

Wheat aphids are major pests during the seed filling stage of wheat. Plant lectins are toxic to sap-sucking pests such as wheat aphids. In this study, Pinellia pedatisecta agglutinin (ppa), a gene encoding mannose binding lectin, was cloned, and it shared 92.69% nucleotide similarity and 94% amino acid similarity with Pinellia ternata agglutinin (pta). The ppa gene, driven by the constitutive and phloem-specific ribulose bisphosphate carboxylase small subunit gene (rbcs) promoter in pBAC-rbcs-ppa expression vector, was transferred into the wheat cultivar Baofeng104 (BF104) by particle bombardment transformation. Fifty-four T0 transgenic plants were generated. The inheritance and expression of the ppa gene were confirmed by PCR and RT-PCR analysis respectively, and seven homozygous transgenic lines were obtained. An aphid bioassay on detached leaf segments revealed that seven ppa transgenic wheat lines had lower aphid growth rates and higher inhibition rates than BF104. Furthermore, two-year aphid bioassays in isolated fields showed that aphid numbers per tiller of transgenic lines were significantly decreased, compared with wild type BF104. Therefore, ppa could be a strong biotechnological candidate to produce aphid-resistant wheat

Simulation and Reconstruction of Runoff in the High-Cold Mountains Area Based on Multiple Machine Learning Models

Runoff from the high-cold mountains area (HCMA) is the most important water resource in the arid zone, and its accurate forecasting is key to the scientific management of water resources downstream of the basin. Constrained by the scarcity of meteorological and hydrological stations in the HCMA and the inconsistency of the observed time series, the simulation and reconstruction of mountain runoff have always been a focus of cold region hydrological research. Based on the runoff observations of the Yurungkash and Kalakash Rivers, the upstream tributaries of the Hotan River on the northern slope of the Kunlun Mountains at different time periods, and the meteorological and atmospheric circulation indices, we used feature analysis and machine learning methods to select the input elements, train, simulate, and select the preferences of the machine learning models of the runoffs of the two watersheds, and reconstruct the missing time series runoff of the Kalakash River. The results show the following. (1) Air temperature is the most important driver of runoff variability in mountainous areas upstream of the Hotan River, and had the strongest performance in terms of the Pearson correlation coefficient (ρXY) and random forest feature importance (FI) (ρXY = 0.63, FI = 0.723), followed by soil temperature (ρXY = 0.63, FI = 0.043), precipitation, hours of sunshine, wind speed, relative humidity, and atmospheric circulation were weakly correlated. A total of 12 elements were selected as the machine learning input data. (2) Comparing the results of the Yurungkash River runoff simulated by eight machine learning methods, we found that the gradient boosting and random forest methods performed best, followed by the AdaBoost and Bagging methods, with Nash–Sutcliffe efficiency coefficients (NSE) of 0.84, 0.82, 0.78, and 0.78, while the support vector regression (NSE = 0.68), ridge (NSE = 0.53), K-nearest neighbor (NSE = 0.56), and linear regression (NSE = 0.51) were simulated poorly. (3) The application of four machine learning methods, gradient boosting, random forest, AdaBoost, and bagging, to simulate the runoff of the Kalakash River for 1978–1998 was generally outstanding, with the NSE exceeding 0.75, and the results of reconstructing the runoff data for the missing period (1999–2019) could well reflect the characteristics of the intra-annual and inter-annual changes in runoff

Hypoxia-treated adipose mesenchymal stem cell-derived exosomes attenuate lumbar facet joint osteoarthritis

Abstract Background Lumbar facet joint osteoarthritis (LFJ OA) is a common disease, and there is still a lack of effective disease-modifying therapies. Our aim was to determine the therapeutic effect of hypoxia-treated adipose mesenchymal stem cell (ADSC)-derived exosomes (Hypo-ADSC-Exos) on the protective effect against LFJ OA. Methods The protective effect of Hypo-ADSC-Exos against LFJ OA was examined in lumbar spinal instability (LSI)-induced LFJ OA models. Spinal pain behavioural assessments and CGRP (Calcitonin Gene-Related Peptide positive) immunofluorescence were evaluated. Cartilage degradation and subchondral bone remodelling were assessed by histological methods, immunohistochemistry, synchrotron radiation-Fourier transform infrared spectroscopy (SR-FTIR), and 3D X-ray microscope scanning. Results Hypoxia enhanced the protective effect of ADSC-Exos on LFJ OA. Specifically, tail vein injection of Hypo-ADSC-Exos protected articular cartilage from degradation, as demonstrated by lower FJ OA scores of articular cartilage and less proteoglycan loss in lumbar facet joint (LFJ) cartilage than in the ADSC-Exo group, and these parameters were significantly improved compared to those in the PBS group. In addition, the levels and distribution of collagen and proteoglycan in LFJ cartilage were increased in the Hypo-ADSC-Exo group compared to the ADSC-Exo or PBS group by SR-FTIR. Furthermore, Hypo-ADSC-Exos normalized uncoupled bone remodelling and aberrant H-type vessel formation in subchondral bone and effectively reduced symptomatic spinal pain caused by LFJ OA in mice compared with those in the ADSC-Exo or PBS group. Conclusions Our results show that hypoxia is an effective method to improve the therapeutic effect of ADSC-Exos on ameliorating spinal pain and LFJ OA progression