Lower back pain and stiffness are the typical symptoms of ankylosing spondylitis (AS). In this study, muscle mass was assessed by muscle density, mechanical elasticity, and area. We investigated the characteristics of lumbar paraspinal-muscle (PSM) mass using muscle ultrasound shear-wave elastography (SWE), as well as the validity of this method for identifying patients with AS.We recruited a representative cohort of 30 AS patients, and 27 healthy volunteers who were age- and sex-matched to the patient study group, investigated the Young’s modulus (YM), cross-sectional area (CSA) and thickness of lumbar multifidus (LM) muscle using SWE. This study did not need to be randomized. Data were collected at the department of ultrasonography of Guangdong Provincial Hospital of Chinese Medicine. We analyzed the data using SPSS version 18.0 . Normal distribution was evaluated by the Shapiro–Wilk test and Q–Q plots. Demographic and baseline data will be analyzed with standard descriptive statistics. Data will be presented as the mean ± standard deviation (SD). Non-normally distributed data are presented as medians with interquartile ranges (IQR).Young’s modulus (YM) of SWE in AS patients was significantly higher than that in volunteers. Percentage change in lumbar multifidus (LM) muscle cross-sectional area (CSA) and thickness were significantly lower in AS patients than in healthy volunteers on the left side of the body. Correlation analysis showed a positive correlation between percentage change in CSA and thickness in both volunteers and AS patients. In AS patients, YM was negatively correlated with percentage change of CSA and thickness on the right side, while increased disease duration in AS was associated with increased YM on the left.AS patients showed reductions in LM muscle mass and function as the disease progressed, SWE could reflect these changes well.Trial registration.http://www.chictr.org.cn/index.aspx.Chinese Clinical Trial Registry, ChiCTR2000031476. Registered 02/04/2020.  Ankylosing spondylitis (AS) is a systemic disease characterized by chronic inflammation of the axial joint involving the sacroiliac joint (SIJ), with primary clinical symptoms of muscle stiffness, limited flexibility, and arthralgia . PatientUltrasound (US) has become part of the fundamental Outcome Measures in Rheumatology (OMERACT) validation methodology, which uses repeated exercises to assess various domains, including inflammatory burden and structural damage , 4 US elMuscle stiffness in this disease typically occurs in lumbar paraspinal-muscles (PSMs). Therefore, we devised a protocol using two-dimensional (2D) acoustic radiation to measure the longitudinal thickness and cross-sectional area (CSA) of lumbar PSMs  as a proxy for muscle force. To correlate lumbar PSM stiffness with muscle force. This highlights the potential of ultrasound SWE as a simple, real-time dynamic, and easily available alternative for the assessment of muscle stiffness in AS and as an extension of clinical rheumatic immune diseases and neuromuscular ultrasound for functional tests. The aim of this study was to show that SWE in a clinical US system with ultrafast algorithms to evaluate tissue composition, 11 and The study was approved by the Institutional Ethics Committee of Guangdong Provincial Hospital of Chinese Medicine . From June 2020 to March 2021, patients and asymptomatic volunteers were prospectively included in our study. This part of non-invasive pilot study, which purpose was to investigate the characteristics of lumbar paraspinal-muscle (PSM) mass using ultrasound (US) shear-wave elastography (SWE), as well as the validity of this method for identifying patients with AS. This study did not need to be randomized. All subjects signed and provided the written informed consent before the experiment. Data were collected at the department of ultrasonography of Guangdong Provincial Hospital of Chinese Medicine.Inclusion criteria for healthy volunteers were as follows: (1) no history of spine-related diseases; (2) no history of chronic lower back pain; (3) moderate body size (BMI ≤ 25), to avoid excessive observation error of the US probe; (4) 18–60 years of age; and (5) provision of written informed consent. Recruitment conditions for patients were as follows: (1) definite diagnosis of axial AS during a stable disease period; (2) 18–60 years of age, with onset age < 40 years; (3) X-ray imaging grade ≤ III; (4) course of disease ≤ 10 years; and (5) willingness to sign informed consent. Potential participants were excluded for the following reasons: (1) clinically important fracture of the spine; (2) spinal deformity or disability; (3) blood coagulation disorder; (4) presence of viral hepatitis, human immunodeficiency virus (HIV), or other blood infection; (5) pregnancy or lactation; (6) previous history of stroke or transient ischemic attacks; (7) pacemaker or other electrical device implanted; or (8) lack of consent, active pursuit of compensation or pending litigation.All volunteers and patients were scanned respectively by two sonographers in a prone position and a state of lumbar multifidus (LM) relaxation. Observer A had 10 years of experience in ultrasonic elastography, and observer B had 5 years of experience in ultrasonic elastography, the two observers specialize in musculoskeletal ultrasound. Each observer was blinded to the data of the other operator and the initial information of the enrolled subjects. The data from the first examination by observer A were used for further statistical analyses. We examined them using a Supersonic MACH 20 Imaging System with a linear-array transducer and a bandwidth of 4–15 MHz . All participants were tested separately on their left and right sides.We measured elasticity, CSA, and LM thickness in the L4–5 horizontal core muscle group of the left and right lumbar spine. A pillow was placed under the subject’s pelvis to reduce lumbar lordosis for accurate measurement of the CSA area and LM thickness. We achieved a transverse plane by holding the transducer perpendicular to the long axis of the abdominal muscles. The lumbar muscle was measured twice: when the subject was relaxed in the prone position, and then again with the subject having one leg prone and the other raised back toward the torso to contract the core lumbar muscle. SWE provides semiquantitative (a color map) and quantitative  imaging biomarkers that are useful in assessing the elasticity of tendon and muscle composition and stiffness . The mapU test and sex using the chi-square test. Young’s modulus (YM) was assessed by the Mann–Whitney U test. Differences in values between resting and contracted LM muscle CSA and thickness, as well as percentage change in LM muscle CSA and thickness, were assessed using an independent-sample t-test. In AS, the relationship among mean YM, percent change in LM muscle thickness, and CSA were assessed using Spearman’s correlation coefficient (SCC). P < 0.05 was considered to indicate a statistically significant difference. To better quantify actual changes, we did not input missing values but used pairwise deletion, and all significance tests were two-tailed with α = 0.05.We analyzed the data using SPSS version 18.0 . Normal distribution was evaluated by the Shapiro–Wilk test and Q–Q plots. We analyzed demographic and baseline data using standard descriptive statistics. For baseline data, we measured BMI using Mann–Whitney Between June 2020 and March 2021, 30 AS patients and 29 volunteers who provided their informed consent were included. We excluded two volunteers, one with a family history of AS and the other with a history of chronic lower back pain. This left 30 AS patients and 27 volunteers for data analysis. The baseline demographic and clinical characteristics were showed in Table vs. 16.40 [11.40–22.50] kPa; Z = –2.901, P = 0.004; right: 22.25 [15.73–38.08] vs. 13.00 [9.90–19.20] kPa; Z = –3.053, P = 0.002). Compared with healthy volunteers, the quality of the LM muscle in AS patients was poor  and 27 volunteers . Figure vs. 28.89 [10.32–38.40] %; Z = –2.333, P = 0.020; right: 16.33 [2.11–29.75] vs. 23.73 [19.14–34.98] %; Z = –1.934, P = 0.053; Fig. Percentage change in LM muscle CSA and thickness were calculated as contracted – rest/rest. Percent CSA change was significantly lower (Wilcoxon rank-sum test) in AS patients than in healthy volunteers on the left side, but there was no significant difference on the right side , but there was no significant difference (independent-sample t test) on the right side  than in healthy controls  and AS patients . In AS patients, YM was negatively correlated with percentage change of CSA  and thickness  on the right of the LM, but we found no significant correlation on the left ; there was also no correlation on either side in healthy controls  or thickness .Correlation analysis , P-CSA difference values  and P-thickness difference values . The Youden index of YM was 0.366 , and the optimal cutoff value difference was 23.05 kPa. The P-CSA Youden index was 0.383 , and the optimal cutoff value difference was 15.78%. The P-thickness Youden index was 0.315 , and the optimal cutoff value difference was 12.75%.The area under the receiver operating characteristic (ROC) curve (AUC) for YM values for identification of AS in all participants is shown in Fig. P < 0.0001) and YM + P-thickness  have higher diagnostic accuracy than YM + P-CSA   disease, which refers to a group of immune-mediated diseases characterized by inflammation of the axial skeleton, peripheral joints, and entheses accompanied by muscle stiffness, causing disability . Joint iMechanical property is an essential factor for maintaining muscle function . MeanwhiConsiderable evidence indicates that US imaging has good to high intrarater reliability for assessing the LM muscles , 24. In The diagnosis of AS is mainly based on symptoms, disease course, and imaging tests; questionnaires and laboratory examination are commonly used in follow-up assessments. However, questionnaires pose the risk of underestimation or overestimation. C-reactive protein (CRP) and erythrocyte sedimentation rate (ESR) are two acute-phase reactants that classically have been used to assess the presence of inflammation in patients. Unfortunately, they are nonspecific and of low sensitivity , especiaThere were several limitations to this study. First, large sample sizes were needed. Second, this was an observational study without other support from imaging or neuroendocrine blood results. Third, technical issues and lack of standardization posed limitations on SWE use in the assessment of tendon injuries.In both AS patients and healthy subjects, correlations between percentage change of CSA and percentage change of thickness were similar, suggesting that the disease did not directly alter their inherent interrelations. By contrast, decreased lumbar-muscle elasticity (the inverse of decrement) was primarily correlated with the percentage change in CSA and thickness in subjects with AS. Whereas, the combined diagnosis of YM and P-thickness seems to be more meaningful for reflecting muscle function and identifying AS diseases. The novel result was that disease and duration differentially affected stiffness and elasticity respectively; this deserves further investigation into the relevant biomechanical properties and their underlying mechanisms. Our results could help guide the development of a specific exercise program to rehabilitate PSMs in the early stages of AS, which might help clinicians better assess balance problems, disability, pain, and degenerative processes of the spine in these patients.


Mavacamten, an allosteric myosin inhibitor, is considered to be a promising drug for the treatment of hypertrophic cardiomyopathy (HCM). This meta-analysis aimed to explore the safety and efficacy of mavacamten in HCM patients.p = 0.01) and the number of patients with a reduction of ≥ 1 NYHA function class . It was found that mavacamten did not significantly affect the Kansas City Cardiomyopathy Questionnaire (KCCQ) , peak oxygen uptake (PVO2) , and ejection fraction (EF)  as compared with placebo. However, KCCQ  and PVO2  improvements were statically significant in the hypertrophic obstructive cardiomyopathy subgroup (HOCM), and a significant decrease in EF  was found in the HOCM subgroup. No significant difference was observed in the incidence rate of serious adverse events between mavacamten and placebo group .A total number of 539 patients were enrolled in four randomized clinical trials. The mean age of patients was 57.9 years and was followed for 29.3 weeks. Pooled analysis showed a significant improvement in clinical response (Log OR = 0.65; Mavacamten proved to be effective and well-tolerated for the treatment of HCM. Mavacamten improved the signs and symptoms of HOCM and decreased EF in these patients without serious adverse events in the clinical trials.The online version contains supplementary material available at 10.1186/s43044-023-00328-7. Hypertrophic cardiomyopathy (HCM) is the most frequent inherited cardiovascular disorder and is responsible for most cases of sudden cardiac death (SCD) in young people, being present in 0.2% of the general population . HCM is There are several therapeutic options for obstructive HCM including β-blockers, the non-dihydropyridine calcium-channel blockers, diuretics, and implantable cardioverter defibrillators (ICDs) , 6. HoweMavacamten  is a novel specific inhibitor of β-cardiac myosin ATPase . MavacamThis promising data led to clinical experimentation and resulted in randomized controlled trials (RCTs) of mavacamten use in HCM patients. Therefore, this systematic review aimed to evaluate safety and efficacy of mavacamten in patients with HCM. A meta-analysis was performed to summarize quantitative data from previous RCTs.We followed the guidelines from Preferred Reporting Items for Systematic Reviews and Meta-analyses  double-blinded randomized clinical trials that the treatment group received placebo and the intervention group received a specified amount of mavacamten, (b) age ≥ 18 years old, (c) adequate data on clinical responses, echocardiogram parameters, Kansas City Cardiomyopathy Questionnaire (KCCQ) score, and serious adverse event at baseline and at the end-point of follow-up in both groups. Non-randomized trials, uncontrolled trials, review studies, case–control, cross-sectional, cohort studies, abstracts, and articles with insufficient data were excluded. No sample size, race, and country restrictions were imposed.2) and at least one NYHA class reduction; or a 30 mL/kg/min or greater improvement in PVO2 and no worsening of NYHA class, NYHA function class, PVO2, ejection fraction (EF), KCCQ score, and serious adverse events during the treatment.Two independent reviewers performed the literature search and checked the eligibility of each study. Collected data items included first author's last name, publication time, duration of intervention, sample size, condition of participant disease (obstructive or non-obstructive hypertrophic cardiomyopathy), mean age, dose of mavacamten used in intervention groups, and the interest outcomes including clinical response defined by a 15 mL/kg/min or greater increase in peak oxygen uptake (PVOWe used the Cochrane risk of bias assessment tool ROB2)  to evalu  to evalI2 and Q statistics [I2 were higher than 50%. Subgroup analysis was performed to explore the possible causes of heterogeneity. P < 0.05 was considered statistically significant.All analysis was performed using STATA, version 16. The odds ratio (OR) and 95% confidence intervals (CI) were calculated for dichotomous outcome indicators. The standardized mean difference (SMD) and 95% CI were calculated for continuous outcome indicators. A random-effects model was used according to between-trial heterogeneity. We assessed heterogeneity using atistics . The hetAs showed in Fig. p = 0.08) and there was significantly heterogeneity between studies (I2 = 81.28%)   Fig. .Fig. 3Fo2 and ≥ 1 NYHA class reduction comparing to baseline, or ≥ 3 ml/kg/min increase in the PVO2 and no worsening of NYHA function class. The forest plot of overall evaluation showed that patients in mavacamten group have more chance of meeting complete clinical response compared with placebo group   Fig. .Fig. 4Fo2 evaluated in two studies. One on HOCM patients and one on non-HOCM patients. The forest plot of overall comparison of PVO2 revealed no statically significant change in the PVO2 , with a significant heterogeneity , but the decrease in the non-HOCM subgroup was not statically significant .PVOp = 0.56, I2 = 0.00%) , with a significant heterogeneity between these two studies (Fig. EF was measured in two studies. One of them was on patients with HOCM, and another study was on patients with non-HOCM. The forest plot of overall comparison of EF between placebo and mavacamten suggested no statically significant change in the EF (SMD = − 0.65, 95% CI − 1.50 to 0.20, ies Fig. . Subgrou2 were controversial. This meta-analysis showed no significant effect for mavacamten use on KCCQ score and PVO2 in patients with HCM. However, the subgroup analysis showed that mavacamten consumption may improve KCCQ score and slightly decrease EF in the HOCM group. Nevertheless, only one study on HCM patients measured EF changes. Therefore, the results about the EF reduction cannot be reliable due to lack of enough data. Besides, our meta-analysis revealed that tolerability outcomes of mavacamten were equal to placebo.Four RCTs allocating 539 participants diagnosed with HCM were included in this study. To the best of our knowledge, this is the first RCT-based meta-analysis evaluating the efficacy of mavacamten among HCM patients. Overall, results indicated that provision of mavacamten improves NYHA function class and clinical response among patients with HCM. Results on the effect of mavacamten administration on KCCQ score and PVOAHA/ACC Guideline recommended that LV wall thickness ≥ 30 mm and late gadolinium enhancement as clinical risk factors for SCD in HCM patients . MoreoveMavacamten has been shown to have a negative inotropic effect that is mediated by direct inhibition of cardiac myosin . The resThis study does have a few limitations. First, the number of RCTs included in this meta-analysis was low. More studies with a larger number of participants are needed to draw definite conclusions. Second, there was some heterogeneity between populations included in this meta-analysis. Third, we analyzed only six indicators and could not able to comprehensively evaluate other factors.2 and KCCQ score in obstructive HCM patients. Administration of mavacamten was associated with no significant serious adverse events.In conclusion, evidence from four RCTs indicated that mavacamten could improve the clinical response and NYHA function class in patient with HCM. Besides, mavacamten administration was associated with enhanced peak VOAdditional file 1. PRISMA checklist.Additional file 2. Risk of bias for included studies.


Patients undergoing knee surgery are at high risk for deep vein thrombosis (DVT), which is infrequent but potentially life-threatening. It has not been identified how to efficiently detect high-risk DVT while minimizing bleeding complications from anticoagulation. We hypothesized that the degree of activation of thrombotic markers may correlate with the size of the thrombus. Therefore, we investigated the correlation between thrombotic markers and DVT thrombus volume in patients after knee surgery.This retrospective study involved 29 patients who underwent around knee osteotomy or total / unicompartmental knee arthroplasty from 2018 to 2020. Fibrin monomer complex (FMC) at 1, and 7 days after surgery, and D-dimer at 4, and 7 days after surgery were investigated. In addition, the volume of DVT was estimated with ultrasonography at the 7 days after surgery. Body mass index, surgical time, and total volume of blood loss were also evaluated. Factors related to thrombus volume were examined statistically.p <  0.001, 95% confidence interval 0.41 to 0.839, r = 0.679).Nine patients (31.0%) exhibited asymptomatic distal DVT, whereas 1 patient (3.4%) experienced asymptomatic proximal DVT. No patients had pulmonary embolism. Statistical analysis showed that only FMC concentration on postoperative day 1 was significantly correlated with thrombus volume (The FMC concentration was a useful early indicator of deep vein thrombosis after knee surgery. Monitoring the FMC concentration could enable selective identification of patients with a high thrombus volume, which is associated with a high risk for pulmonary embolism. Several surgical options are available for patients with knee osteoarthritis (OA), such as osteotomy, unicompartmental knee arthroplasty (UKA), and total knee arthroplasty (TKA). The choice of surgery is dictated by the degree of deformation, patient lifestyle and activity level. However, various complications have been reported with these surgeries, including venous thromboembolism (VTE), infections, fractures , 2, and Due to the potential danger associated with DVT, many studies have examined approaches for its prevention and early detection. Fibrin-related markers such as D-dimer and soluble fibrin (SF) / fibrin monomer complex (FMC) are recognized as laboratory tests to assist in the detection of VTE . A D-dimSince most PE which occurs after knee surgery originates from DVT, the size of the DVT may be related to the severity of PE. When a large thrombus is formed, significant activation of the coagulation/fibrinolysis system occurs. Therefore, we hypothesized that thrombotic markers may correlate with thrombus volume.Hence, the correlation between thrombotic markers and DVT thrombus volume during the perioperative period in patients who underwent knee surgery was investigated in the present study.This retrospective study involved 29 patients who underwent around the knee osteotomy (AKO), TKA, UKA due to medial OA or spontaneous osteonecrosis of the knee from April 2018 to March 2020. A total of 12 men and 17 women were enrolled in the study; mean age of the patients was 68.5 years (range 54–83 years), the number of patients in each surgery were AKO:TKA:UKA = 16:9:4. AKO included medial open-wedge high tibial osteotomy, lateral closed-wedge high tibial osteotomy, distal femoral osteotomy, and the combination of femoral and tibial osteotomy (double-level osteotomy). Tourniquet was used in TKA / UKA. No patients had previous history of DVT or PE, and none of the patients received preoperative anticoagulant therapy. All surgeries were performed by 2 experienced orthopaedic surgeons. All patients received post operative physical prophylaxis. Postoperative anticoagulation  was given for 14 days only to TKA and UKA patients according to Japanese insurance indications.Age, body mass index (BMI), surgical time, and total blood loss during the operation were recorded as the patients’ characteristics. In addition, FMC at 1, and 7 days after surgery , and D-dimer at 4, and 7 days after surgery  were measured.Duplex doppler US investigations were employed to investigate for the presence of DVT at 7 days after surgery. DVTs were classified as proximal or distal depending on whether the thrombus was located above or below the popliteal vein, respectively. Thrombus volume was calculated by approximation to an elliptic cylinder based on the US measurement  Fig. 1)1). If sep <  0.05 considered statistically significant.All data were expressed as mean ± standard deviation (SD). The normal distribution of the evaluation items was tested by Kolmogorov-Smirnov test. Pearson correlation coefficient was used to examine the relationship between each evaluation items and thrombus volume. All statistical analyses were performed using EZR software , with p p = 0.06). Thrombus locations were as follows: common femoral vein, 1; posterior tibial vein, 3; peroneal vein, 1; soleus vein, 6  (Table Kolmogorov-Smirnov test revealed that FMC D1 and D7 were non-normally distributed, but log-normally distributed. So, these data were log-transformed and used for statistical analysis. As a results of Pearson correlation coefficient, only FMC D1 was correlated with the thrombus volume (No markers have been found correlate with the size of post-operative DVT which can result in PE. In the present study, we revealed for the first time that the author know of, FMC D1 was strongly correlated with the volume of DVT thrombus in knee surgery patients. Additionally, routine anticoagulant prophylaxis tended to decrease the prevalence of DVT in patients of TKA/UKA compared to osteotomy patients. However proximal DVT was observed in TKA patient.Previous report suggested that postoperative routine prophylaxis with anticoagulants has shown some efficacy . HoweverFurthermore, this selective intervention method may have cost-effective advantages. Recent systematic reviews showed that the combination of D-dimer and US are cost-effective method for the diagnosis of DVT , 28. HowHowever, the present study has several limitations. First, there is no cut-off value for the thrombus volume causing severe PE. The short-term mortality of PE is reported to be related to the right ventricle / left ventricle ratio as well as the thrombus volume , hence tFMC concentration on postoperative day 1 was a useful early indicator of DVT volume after knee surgery. Monitoring FMC could enable selective identification of patients with a high thrombus volume, which is associated with a high risk for pulmonary embolism.


Astragalus Membranaceus, Ganoderma lucidum, Inonotus obliquus, and Momordica charantia L., is a specially designed Chinese medicine formula to treat type 2 diabetes (T2D). In this study, a mouse model of T2D induced by high-fat diet and streptozotocin was used to explore the mechanism of HQLHS in improving hyperglycemia and hyperlipidemia through multiple rounds of animal experiments, such as HQLHS feeding, fecal microbiota transplantation (FMT), and live bacteria feeding, so as to explore the potential target intestinal flora in its hypoglycemic effect. Results show that such specific taxa as Bifidobacterium, Turicibacter, Alistipes, Romboutsia, and Christensenella were identified to be preferably enriched by HQLHS and then assumed to be the target microbes. Herein, FMT was used to test if the upregulated beneficial bacteria by HQLHS play a therapeutic role. The strain Christensenella minuta DSM 22607 and the strain Christensenella timonensis DSM 102800 were selected to test the beneficial effect of Christensenella taxa on T2D. Diabetic animals supplemented with these strains showed the improvement in blood glucose and lipid metabolism, the promotion of GLP-1 secretion, the increase in antioxidant capacity, the inhibition of hepatic gluconeogenesis, the suppression of intestinal glucose absorption, the enhancement of intestinal barrier, reduced LPS-induced inflammation, and the reduction of branched amino acids (BCAAs) content in the liver. Overall, these data demonstrate that Christensenella plays a beneficial role in T2D and is a target for the action of HQLHS therapy.There is a lot of evidence that oral hypoglycemic drugs work by affecting gut microbes, but the key strains responsible for this effect are not well known. Huang-Qi-Ling-Hua-San (HQLHS), composed of  Type 2 Diabetes (T2D) is a complex endocrine and metabolic disease characterized by hyperglycemia. T2D causes varying degrees of insulin resistance, pancreatic β cell dysfunction, low-grade systemic inflammation, intestinal flora imbalance, and other endocrine disorders under the interaction of genetic and environmental factors . The gloRecently, studies on the pathogenesis and therapeutic targets of T2D have focused on the structure of the intestinal microflora in humans and animal models . ManipulTraditional Chinese medicine (TCM) is an important form of complementary medicine that has become an attractive strategy in the treatment of diabetes . Since iAstragalus membranaceus improves cognitive dysfunction in diabetic mice by altering gut microbiota, such as dramatically enriching the abundance of Lactobacillus and Sutterella in the gut. A polysaccharide in Ganoderma lucidum improved to be effective in improving glucose and lipid metabolism, reducing inflammation, and increasing the relative abundance of short-chain fatty acid (SCFA)-producers  interacts with host cells through Metabolism-Associated Molecular Patterns (MAMPs) to modulate the immune response  protein, which may regulate bile acid circulation in the host. Many studies have found that Christensenellaceae are negatively correlated with the pathologies typical of metabolic syndrome, however, the underlying mechanism has not been fully explained. Thus, Christensenellaceae strains as the next generation of probiotics being developed, and it is necessary to explain how they play a beneficial role in the intestinal ecosystem . The four kinds of medicinal materials were pulverized and screened, respectively, and mixed at a ratio of 2:1:1:1.For the preparation of HQLHS: The detection of the main components was entrusted to Beijing Novogene Co. Ltd., performing by high-performance liquid chromatography-triple quadrupole linear ion trap tandem mass spectrometry (HPLC-QTrap-MS/MS) based on the highly sensitive SCIEX QTRAP® 6500+ mass spectrometry platform. Quantitative data acquisition was accomplished in multiple reaction monitoring (MRM) mode, and further identification of target compounds was achieved by ultra-performance liquid chromatography-quadrupole-time-of-flight mass spectrometry. HPLC parameter: the Waters XselectTM HSS T3, 2.5 μm, 2.1 mm × 150 mm column, mobile phase A 0.1% formic acid, mobile phase B 0.1% formic acid-acetonitrile, 50°C, 0.4 ml/min gradient elution.Christensenella minuta DSM 22607 and Christensenella timonensis DSM 102800 were purchased from the German Collection of Microorganisms and Cells Cultures (DSMZ). Both strains were cultured in Reinforced Clostridial Medium (BD Difco/BBL) under anaerobic conditions at 37°C and obtained by centrifugation  after 4 days. After washing three times with normal saline, the solution was diluted into 1 × 109 cfu/ml for intragastric administration.Specific pathogen-free (SPF) male C57BL/6 J mice  were purchased from Vital River Laboratory Animal Technology Co., Ltd. . Normal diet feed (TP 23402) and 60% high-fat feed (TP 23400) were purchased from TROPHIC Animal Feed High-tech Co., Ltd. All animals were maintained in accordance with the laboratory animal guidelines, and the animal experiments were approved by the Institutional Animal Care and Use Committee of Jilin University (Permission Number: 2018-SY1005).n = 10). For the remaining 13 weeks, 10 mice in the normal control (NC) group were fed with normal diet and the other 30 mice were fed with 60% high-fat diet. The 30 high-fat diet mice were intraperitoneally injected with STZ  by the fourth week. Meanwhile, NC group was injected with citrate buffer. One week after the STZ injection, tail blood was collected to measure fasting blood glucose (FBG). Mice with fasting blood glucose >11.1 mmol/L were considered to have T2D. After the fifth week, the diabetic mice were treated by gavage once a day with normal saline (DM), 300 mg/kg/metformin dissolved in normal saline (MET) and 800 mg/kg HQLHS dissolved in normal saline (DM-HQ).After 1 week of acclimation, the animals were randomly divided into four groups (n = 10). The NC group received normal saline and the NC-HQ group received 800 mg/kg/day HQLHS dissolved in normal saline. Both groups were fed with a normal diet. The remaining 30 mice were kept on a 60% high-fat diet and, as in Part I, after the fourth week they were intraperitoneally injected with 120 mg/kg STZ. After the fifth week, T2D mice (FBD > 11.1 mmol/L) were treated by gavage once a day normal saline daily (DM), 300 μl bacterial suspension (FMT), and 800 mg/kg HQLHS dissolved in normal saline (DM-HQ) by gavage once a day. At the fifth week, fecal samples were obtained from the NC-HQ group every day for FMT. Samples were homogenized and suspended in the normal saline (500 mg in 5 ml) followed by centrifugation at 800 rpm for 3 min. Each FMT group mouse was daily gavaged 300 μl bacterial suspension.After 1 week of acclimation, the animals were randomly divided into five groups (Christensenella minuta DSM 22607 (1 × 109 cfu/ml) suspension (CM), and Christensenella timonensis DSM 102800 (1 × 109 cfu/ml) suspension (CT), where each strain was suspended in normal saline.After 1 week of acclimation, all the animals were fed with 60% high-fat diet throughout the experiment. The modeling method of T2D induced by STZ is described in Part I. After the fifth week, T2D mice were treated by gavage once a day with 300 μl of normal saline (DM), The oral glucose tolerance test (OGTT) was measured at week 11. After 12 h of fasting, mice were orally administered with 2.0 g/kg glucose, and tail vein blood samples were collected for testing after 0, 30, 60, 90, and 120 min. Blood glucose levels were measured using a SUNNUO glucometer .via ocular sampling after the experiment and the serum was obtained by centrifugation of blood samples at 3,000 × g for 15 min at 4°C. The epididymis fat, liver, pancreas, ileum, colon, and cecal contents were collected after dissecting the mice. Part of the liver, colon, and pancreas were preserved in 4% paraformaldehyde for morphological observation by H&E staining. The remaining tissues and the cecal contents were stored at −80°C for further study.After the last administration, fresh feces were collected and preserved at −80°C for 16S rDNA sequencing. Blood was collected Biochemical analyses of serum and liver samples included liver glycogen, aspartate aminotransferase (AST), alanine aminotransferase (ALT), superoxide dismutase (SOD), glutathione peroxidase (GSH-Px), catalase activity (CAT), malondialdehyde (MDA), total cholesterol (T-CHO), triglyceride (TG), low-density lipoprotein cholesterol (LDL-C), and high-density lipoprotein cholesterol (HDL-C) using commercially available assay kits . Serum Insulin (INS), glucagon-like peptide-1 (GLP-1), and lipopolysaccharide (LPS) were detected using the enzyme-linked immunosorbent assay (ELISA) kit  according to the manufacturer’s instruction.The total RNA extraction, RT-PCR, and qPCR process were performed as described . The priSamples  of mice belonging to the same cage were mixed and treated as one sample (according to the coprophagic character of the mice) for testing. Three samples were obtained from each group of mice. Bacterial DNA was extracted from the cecal contents for 16S rDNA gene sequencing analysis. Detailed procedures of 16S rDNA gene V3–V4 region sequencing and data processing were followed a previous report . The V3–1H NMR spectra were acquired using CPMG, with relaxation delay of 3 s and a mixing time of 0.1 s. Sixty-four free induction decays (FIDs) were collected into 64 K data points and an acquisition time of 2 s. FIDs were zero-filled to 64 K prior to Fourier transformation.NMR data acquisition and processing were performed as described . Data cog, 4°C), the supernatant of each sample was collected. The above process was repeated twice. The supernatant of each sample was combined and centrifuged again for 10 min. After methanol was removed under vacuum, the supernatants of each sample were freeze-dried, producing hydrophilic extracts of liver. The samples obtained were hydrophilic extracts of liver. The remaining solid residue of each tissue sample was transferred to a new EP tube, extracted with 1.8 ml precooled chloroform, and the mixture was treated with five intermittent ultrasound treatments (60 s ultrasound/60 s crushing). After centrifugation , the chloroform layer was collected carefully. The process was repeated twice, and the combined layer was centrifuged again for 10 min. Chloroform was removed from the sample supernatant under vacuum to obtain the lipophilic extract of the liver.Sample preparation was performed as described , with sop < 0.05) was used to evaluate the variable contribution and to identify the potential biomarkers. MetaboAnalyst was applied to screen out important metabolic pathways related to differential metabolites, which were obtained by KEGG.NMR raw data were preprocessed by MestReNova 10.0. The statistical strategy adopted for the analysis of the samples involved a preliminary unsupervised Principal Component Analysis (PCA), followed by a supervised pairwise Orthogonal Projection to Latent Structures Discriminant Analysis (O2PLS-DA) using SIMCA 14.0 . To validate the models, random permutation testing (200 randomizations) was then applied. The Variable Importance in the Projection (VIP) value  and performed with Origin 2018 . Visual network diagram was performed on Cytoscape_3.9.0. The area of the pancreatic islets of Langerhans was calculated by Auto CAD 2021. Hierarchical clustering tree and Principal co-ordinates analysis (PCoA) plots were generated by the ggplot2 packages of the R software (version 3.3.1). Differentially abundance of genera across groups was calculated using an extended error bar plot using STAMP (Ver. 2.1.3). LEfSe analysis was performed on The determination of the main components of Chinese medicine prescription is to expound its pharmacodynamic substance basis in this study. In HQLHS, 1596 components were detected by LC–MS , consistIn order to explore the anti-diabetes effect of HQLHS, the part I animal experiment was designed , where tTo investigate the effect of HQLHS on gut microbiota, we analyzed the cecal content flora of the four groups of mice. HQLHS supplementation did not significantly change the overall gut microbiota abundance in the diabetic mice, as shown by α diversity , whereasBacteroidetes, Firmicutes, and Proteobacteria were predominant phyla in the cecal flora  and collected the feces from NC-HQ mice at week 0 [NC-HQ(0)] and at week 4 NC-HQ;  for 16S Turicibacter, Alistipes, Bifidobacterium, Romboutsia, Christensenella, uncultured_bacterium_f_Christensenellaceae, Ruminococcaceae_UCG-013, and Prevotella_1 were significantly upregulated, while Akkermansia, Roseburia, and Blautia were significantly downregulated. In contrast, the relative abundance of Faecalibacterium was significantly increased, while Ruminococcaceae_NK4A214_group was significantly reduced. The differences in the intestinal flora may be due to different diets in the NC and DM groups, and to individual differences in the different batches of mice may lead to different intervention effects of HQLHS on intestinal flora. In addition, the relative abundance of Escherichia-Shigella, Tyzzerella, Bacteroides, and Alloprevotella was significantly decreased. After HQLHS intervention, according to the linear discriminant analysis (LDA) value  value , TuricibTuricibacter, Alistipes, Bifidobacterium, Romboutsia, Christensenella, and certain taxa of Ruminococcaceae.Combined with the Part I work, these results show that HQLHS intervention consistently increased After week 5, we collected feces of NC-HQ mice, and transplanted daily to the diabetic mice. The Part II experimental design is shown in Lachnospiraceae and Ruminococcaceae were significantly altered after the fecal microbiota transplantation  and Christensenella timonensis DSM 102800  mice, incomplete colonization of low-incidence T1D fecal flora did not change the potential incidence of diabetes, but the incidence was reduced when the key strain  species . Currentyte size . The bidntration . The abuimmunity . RuminocR levels ; Notablyd leptin . Our stuChristensenella on HFD and STZ induced diabetic mice. The two strains, C. minuta DSM 22607 and C. timonensis DSM 102800, improved diabetes-related indicators. Oxidative stress plays an important role in the development of T2D , stimulating insulin secretion and regulating glucose homeostasis , inducing innate immune responses, plays an important role in metabolic disorders and may be a trigger for the onset of insulin resistance  and related metabolites have emerged as one of the strongest biomarkers for a range of cardiometabolic and related diseases, including obesity, insulin resistance, T2D, and coronary artery disease  can be found at: The animal study was reviewed and approved by Experimental Animal Welfare and Ethics Committee of School of Life Sciences, Jilin University.TP: conceptualization, investigation, visualization, and writing—original draft preparation. SZ, WZ, CS, KN, and QZ: investigation. YX: resources and supervision. HX and QX: conceptualization, resources, supervision, and writing—review and editing. All authors contributed to the article and approved the submitted version.This work was supported by the Department of Science and Technology of Jilin Province under (grant nos. 20200708072YY and 20210401122YY).The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.


Inactive behaviour is common in older adults during hospitalisation and associated with poor health outcomes. If patients at high risk of spending little time standing/walking could be identified early after admission, they could be given interventions aimed at increasing their time spent standing/walking. This study aims to identify older adults at high risk of low physical activity (PA) levels during hospitalisation.Prospective cohort study of 165 older adults (≥ 70 years) admitted to the department of Internal Medicine of Maastricht University Medical Centre for acute medical illness. Two prediction models were developed to predict the probability of low PA levels during hospitalisation. Time spent standing/walking per day was measured with an accelerometer until discharge (≤ 12 days). The average time standing/walking per day between inclusion and discharge was dichotomized into low/high PA levels by dividing the cohort at the median (50.0%) in model 1, and lowest tertile (33.3%) in model 2. Potential predictors—Short Physical Performance Battery (SPPB), Activity Measure for Post-Acute Care (AM-PAC), age, sex, walking aid use, and disabilities in activities of daily living—were selected based on literature and analysed using logistic regression analysis. Models were internally validated using bootstrapping. Model performance was quantified using measures of discrimination (area under the receiver operating characteristic curve (AUC)) and calibration (Hosmer and Lemeshow (H–L) goodness-of-fit test and calibration plots).Model 1 predicts a probability of spending ≤ 64.4 min standing/walking and holds the predictors SPPB, AM-PAC and sex. Model 2 predicts a probability of spending ≤ 47.2 min standing/walking and holds the predictors SPPB, AM-PAC, age and walking aid use. AUCs of models 1 and 2 were .80  = .73—.87) and .86 (95%CI = .79—.92), respectively, indicating good discriminative ability. Both models demonstrate near perfect calibration of the predicted probabilities and good overall performance, with model 2 performing slightly better.The developed and internally validated prediction models may enable clinicians to identify older adults at high risk of low PA levels during hospitalisation. External validation and determining the clinical impact are needed before applying the models in clinical practise.The online version contains supplementary material available at 10.1186/s12877-022-03146-9. Older adults admitted to hospital with an acute medical illness show high prevalence of multimorbidity and age-related impairments, such as malnutrition, cognitive impairment, incontinence, and sensory impairment . CombineInactive behaviour during hospitalisation is strongly associated with functional decline , 12–14, To our knowledge, a prognostic tool that predicts a patient’s probability of spending little time standing and walking during hospitalisation has not been developed yet. However, in recent years the number of studies investigating physical activity (PA) behaviour of older adults admitted to a hospital with an acute medical illness has grown and more insight has been gained in factors associated with inactive behaviour during hospitalisation , 19–22. This single centre, prospective cohort study was conducted at the department of Internal Medicine of Maastricht University Medical Centre (MUMC +) in Maastricht, the Netherlands, between October 2018 and March 2020. The Transparent Reporting of a multivariable prediction model for Individual Prognosis or Diagnosis (TRIPOD) statement was used as reporting guideline  , 25. ExcThe following criteria were established through performing a brief screening with the attending physician prior to the informed consent procedure: age, admission for an acute medical illness, presence of contraindications to walking or wearing an accelerometer, mental incapacity, and life expectancy. Remaining criteria were checked by patient report.0). PA was monitored with the MOX activity monitor . The device contains a tri-axial accelerometer sensor  in a small waterproof housing . Raw acceleration data (± 8 g) were measured by three orthogonal sensor axes  at a 25 Hz sampling rate. PA was measured in time spent standing/walking as this was deemed a more appropriate sensor based outcome variable for hospitalised older adults than intensity levels or step counts[1).PA monitoring started immediately after informed consent was obtained , days with ≥ 20 h of wear time were included in the analysis. MATLAB (version 9.5 (R2018b) Natick, Massachusetts: The MathWorks Inc.: Natick, MA, USA; 2018) was used to calculate the number of minutes spent standing/walking per day. Subsequently, the average number of minutes spent standing/walking per day between t0 and t1 was dichotomized into low and high PA levels. Clinical guidelines stipulating the amount of time patients should to be standing/walking during hospitalisation do not exist yet [0 and t1 was dichotomized into low and high PA levels by dividing the cohort at the median, categorizing 50.0% of the patients as having low PA levels. For development of model 2, the cohort was divided at the lowest tertile, categorizing 33.3% of the patients as having low PA levels. The use of accelerometers allowed the assessment of low or high PA levels between t0 and t1 to remain blinded.For prediction model development, the average number of minutes spent standing/walking per day between txist yet , 28–31. xist yet –34. As ixist yet , 19, 35.Potential predictors were preselected based on published studies reporting factors associated with inactive behaviour of older adults admitted to a hospital with an acute medical illness , 19, 20.Functional mobility was assessed by the researcher immediately after PA monitoring had started, using the SPPB and AM-PAC. The SPPB is a performance based tool to measure physical performance by assessing balance, walking speed and lower extremity strength , 37. It  The AM-PAC Inpatient Basic Mobility short form assesses the following daily activities: turning in bed, sitting down and standing up, moving from lying to sitting, moving from a bed to chair, walking and climbing stairs. Climbing stairs was left out of the analysis as not every patient needs to climb stairs at home. This provided a total score between 1 and 20 points, dichotomized into dependent (≤ 19 points = 0) versus independent mobility (20 points = 1) based on receiver operating characteristic (ROC) curve analysis. The AM-PAC is short and easy to use. It shows large inter-rater reliability and test–retest reliability , 40 and 0. It rates the patient’s performance of six activities  on a dichotomous scale (dependent/independent) [0. Disabilities in ADL two weeks preceding admission were reported on the Katz Index of Independence in Activities of Daily Living (Katz ADL) at tpendent) , 43. Thependent) . Further1, the following data was extracted from the electronic health record: clinical diagnosis of the current hospitalisation based on the ICD-11[At the ICD-11, number This study initially aimed to develop only one model, categorizing 50.0% of the patients as having low PA levels. Therefore, the sample size calculation was based on model 1. Post-hoc discussions regarding optimal cut-off values of low PA levels resulted in the development of a second model, enabling the comparison of different cut-off values. Six potential predictors were preselected. Because ‘walking aid use preceding hospitalisation’ has a categorical outcome containing three categories it had to be counted double, resulting in a sample size calculation based on seven potential predictors. It is recommended that at least 10 events should be collected per potential predictor . An evenData were checked for completeness and inconsistencies. Any inconsistencies or incomplete data were corrected or completed. Missing values were imputed using stochastic regression imputation with fully conditional specification , 48. To P-value < 0.05 was used to indicate statistical significance.Characteristics of patients were compared between the low and high PA level groups. To compare proportions, the chi-square test was used. For continuous variables, the independent samples t-test or Mann–Whitney U test was used for normally and not-normally distributed data, respectively. A P-value of 0.20 was used to prevent too early deletion of potentially relevant predictors [The models were developed using ‘low PA levels during hospitalisation’ as the outcome variable. Multicollinearity of potential predictor variables was checked using collinearity diagnostics  and tolerance). Additionally, continuous variables were checked for having a linear association with the log odds of the outcome. For model 1, all seven predictors were introduced in a multivariable logistic regression model. For model 2, only five predictors could be introduced as the sample size was based on model 1 and the prevalence of low PA levels was lower in model 2. Therefore, univariable regression analysis was performed as additional step to select five potential predictors. To reduce the number of predictors in the multivariable logistic regression models, backward stepwise elimination based on the Wald test was used. A liberal edictors .B-bootstrap samples of the same size as the original sample (B = 1000 was used) were drawn with replacement from the original data, reflecting the drawing of samples from the underlying population. A shrinkage factor was estimated to adjust the model coefficients in order to make future predictions less extreme. After shrinkage, the model intercepts were re-estimated to prevent systematic under- or overestimation of risks.The models were internally validated using bootstrapping. R2 and the Brier score. The ability of the models to discriminate between patients with low and high PA levels during hospitalisation was quantified as the area under the receiver operating characteristic curve (AUC). Additionally, sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) were calculated for a selection of probability cut-off values. To classify patients as being at high risk of low PA levels during hospitalisation, a probability threshold can be used. Patients are considered at high risk if their predicted probabilities are at or above this threshold. In order to have a low rate of patients misclassified as being at low risk , a probability threshold yielding a high NPV, but acceptable PPV, was chosen per model.Overall performance of both models was assessed using Nagelkerke's www.r-project.org).The agreement between predicted probabilities and observed frequencies of the outcome (accuracy) was assessed by visually inspecting the calibration plot. Furthermore, a Hosmer and Lemeshow (H–L) goodness-of-fit statistic was computed, with non-significant H–L statistics indicating good model fit. All statistical analyses were performed using SPSS version 23.0.0.2  and R version 4.0.4  dropped out and data of 146 patients was used in the analysis ) was 81.3 (6.8) years and 86 (58.9%) patients were male. The group of patients were median (± Interquartile Range (IQR)) 64.4 (34.8 – 100.1) minutes standing/walking per day and 33.3% of the patients were ≤ 47.2 min standing/walking per day. The characteristics of study participants are reported in Table In the dependent variable ‘number of minutes spent standing/walking per day’, data was missing for 72 out of 949 measurement days (7.5%), spread over 27 patients (18%). Main reasons for missing values were the accelerometer falling off, getting lost or malfunctioning. Data of all other variables was complete. After imputation, data of all 146 patients was complete for development of the prediction model.For development of model 1, all predictors were entered in the multivariable regression model . For development of model 2, univariable regression analysis was first performed on all potential predictors, after which SPPB, AM-PAC, age, and walking aid use preceding hospitalisation were entered in the multivariable regression model. Table p = 0.755 and p = 0.209). Overall, model 2 showed a slightly better performance.All model performance measures are shown in detail in Additional file A selection of probability cut-off values and their corresponding sensitivity, specificity, PPV and NPV are reported in Additional file The sensitivity analyses showed similar results for the imputed and the original non-imputed data sets and we conclude that imputation did not result in large differences.In this study we developed and internally validated two prediction models that can be used to predict the probability of low PA levels during hospitalisation for older adults admitted to a hospital with an acute medical illness. The first model predicts a patient’s probability of spending less than an average of 64.4 min standing/walking per day and holds three predictors: SPPB, AM-PAC and sex. The second model predicts a patient’s probability of spending less than an average of 47.2 min standing/walking per day and holds four predictors: SPPB, AM-PAC, age and walking aid use preceding hospitalisation. Both models showed good discriminative ability and accurate prediction of spending little time standing/walking during hospitalisation, with the second model performing slightly better.To our knowledge, this is the first study that aims to identify older adults at high risk of spending little time standing/walking during hospitalisation. One of the challenges in developing a suitable prediction model was the lack of criterion-referenced cut-off values regarding the classification of low or high PA levels , 28–31. PA was measured in time spent in different activities , as this was deemed a more meaningful sensor based outcome variable for hospitalised older adults than intensity levels (activity counts) or step counts . First, The developed models show that functional assessments combined with easily acquired clinical parameters have potential to identify patients at high risk of low PA levels during hospitalisation. As we felt it important that patients at high risk would not miss out on an intervention, we opted for models with low rates of false-negative predictions. In choosing a probability threshold for each model we therefore aimed for a high NPV and accepted a higher rate of false-positive predictions.Using model 1 with a probability threshold of 0.41 resulted in misclassification of 8.9% of all patients as being at low risk of spending less than 64.4 min standing/walking . Moreover, 20.6% were misclassified as being at high risk  and would be given an intervention while actually having high PA levels. The predictive abilities of model 2 are slightly better, resulting in less misclassifications. Using model 2 with a probability threshold of 0.30 will result in a 4.8% false-negative prediction rate and a 15.1% false-positive prediction rate of spending less than 47.2 min standing/walking.However, a certain level of misclassifications seems inevitable when predicting the PA behaviour of hospitalised patients early after admission. Previous studies have shown that the PA behaviour of hospitalised patients is influenced by many different factors, such as complications or symptoms developing throughout the hospital stay, patient motivation, using medical devices that limit walking , referral to physiotherapy, or a lack of availability of healthcare staff to provide assistance during walking –61. As sIn retrospect, we consider the rate of misclassifications of both models acceptable for use in clinical practice. Although performance of model 2 was slightly better, the choice for either one of the models depends on whether roughly one hour or three quarters of an hour standing/walking are preferred as cut-off value for low PA levels during hospitalisation. Moreover, it also depends on the availability of resources, as model 1 will classify more patients as being at high risk of low PA levels.The present study has several strengths, including a prospective data collection, recruitment of consecutive patients, and inclusion of patients with mild cognitive impairments. Moreover, all predictors were selected from literature based on previous evidence , 19, 20 We also recognise several limitations. First, with the current study design we cannot determine if patients changed their time spent standing/walking due to potential confounding factors that were unknown early after admission, such as receiving physiotherapy guidance or complications which may have developed during hospital stay. Second, we initially aimed to develop one prediction model. Due to post-hoc discussions regarding an optimal cut-off value we decided to develop a second model as well, enabling the comparison of different cut-off values. The power calculation was originally meant for model 1, allowing for seven potential predictors and an event rate of 50.0%. Because the event rate of model 2 was 33.3%, only five potential predictors could be introduced in the analysis. To prevent overfitting of the model by introducing to many predictors, univariable analysis had to be performed as an additional step. Third, we dichotomized the categorical AM-PAC and Katz ADL outcomes to improve the clinical applicability, which may have led to loss of information. Lastly, the algorithm of the MOX activity monitor is unable to differentiate time spent standing from time spent walking. This limited the development of a prediction model that can be used to identify older adults at high risk of spending little time walking during hospitalisation.The developed prediction models can be used in clinical practice by performing a simple screening early after admission, consisting of two functional assessments combined with self-reported information. The prediction models can be adapted into an easy-to-use calculator that can be used during screening. Using the prediction models to identify patients at high risk of low PA levels early after admission is an important first step in preventing the negative effects associated with spending little time standing/walking during hospitalisation. Patients at high risk can subsequently be given interventions aimed at increasing their time spend standing/walking. However, as few studies have investigated the efficacy of interventions aimed at increasing the PA behaviour of older adults during hospitalisation, further research is advised, comparing different types of interventions and with detailed reporting of frequency, intensity and duration , 29–31. We developed and internally validated two prediction models that can be used to predict the probability of low PA levels during hospitalisation for older adults admitted to a hospital with an acute medical illness. Both models showed a good overall performance, with a good discriminative ability and accurate prediction of low PA levels. This study showed that both models hold promise as prediction tools that enable clinicians to accurately identify older adults at high risk of low PA levels during hospitalisation.Additional file 1. TRIPOD checklistPrediction Model Development. Checklist for transparent reporting of amultivariable prediction model for individual prognosis or diagnosis (TRIPOD):The TRIPOD statement.Additional file 2. Performance of theprediction models. Model performance measures of the two prediction models forpredicting the probability of low physical activity levels duringhospitalisation for older adults admitted to a hospital with an acute medicalillness.Additional file 3. Calibration plots. Calibrationplots with the observed frequency of low physical activity levels by predictedprobability of model 1 and 2.Additional file 4. Probability cut-offvalues model 1. Sensitivity, specificity, positive predictive value, andnegative predictive value for low physical activity levels duringhospitalisation at a selection of consecutive cut-off points of the predictedprobability of model 1.Additional file 5. Probability cut-offvalues model 2. Sensitivity, specificity, positive predictive value, andnegative predictive value for low physical activity levels duringhospitalisation at a selection of consecutive cut-off points of the predictedprobability of model 2.


There was no significant difference in the overall accuracies of BioFire and Luminex assays (P = 0.6171); however, significant differences were found between BioFire and GenMark (P = 0.0003) and between GenMark and Luminex (P = 0.0009). The positive percent agreement of the BioFire RP assay was 94.1%, compared to 97.3% for GenMark RVP and 96.5% for Luminex RPP. Overall negative percent agreement values were high for all three assays, i.e., 99.9% for BioFire and Luminex and 99.5% for GenMark. The three assays were equivalent for adenovirus, human metapneumovirus, influenza A, and respiratory syncytial virus. Increased false-positive results were seen with BioFire for the endemic coronaviruses and with GenMark for influenza B and the parainfluenza viruses.This study compares three of the most inclusive and widely used panels for respiratory syndromic testing in the United States, namely, Luminex NxTAG Respiratory Pathogen Panel (RPP), BioFire FilmArray Respiratory Panel (RP), and GenMark eSensor Respiratory Viral Panel (RVP). We compared the three assays using nasopharyngeal swab samples (IMPORTANCE Clinical laboratories have multiple choices when it is comes to syndromic respiratory testing. Here, the Luminex NxTAG RPP is compared to the BioFire FilmArray RP and GenMark eSensor RVP for overall and per-target accuracy. As new tests come to market, it is important to ascertain their performance characteristics, compared to other widely used in vitro diagnostic products. Acute respiratory infections continue to be major drivers of health care visits in the United States. While overall mortality rates due to influenza and pneumonia have been decreasing , the burThe three most inclusive respiratory pathogen panels (RPPs) cleared by the FDA at the time of this study are the FilmArray Respiratory Panel (RP) , the eSensor Respiratory Viral Panel (RVP) , and the NxTAG RPP  . Separat10–Of the 350 NP swab samples tested, 199 were consensus positive for a single viral target, 24 were positive for two viral targets, and 3 were positive for three viral targets . No sampP = 0.9728). Overall negative percent agreement (NPA) was high for all three assays, i.e., 99.9% for BioFire and Luminex and 99.5% for GenMark. To determine the overall performance, the total number of possible results was established by multiplying the number of targets detectable  by the number of NP swab samples tested (n = 350). PPA was 94.2% for BioFire, 96.3% for Luminex, and 97.3% for GenMark. NPA was consistent at 99.6% (GenMark) and 99.9% (BioFire and Luminex).Overall positive and negative agreements were calculated for each assay. To compare the assays fairly, the metrics were assessed for the 16 targets they have in common, omitting bocavirus and the bacterial pathogens. The positive percent agreement (PPA) of the BioFire RP assay was 94.1%, compared to 97.3% for GenMark RVP and 96.5% for Luminex RPP. Chi-square analysis found no dissimilarity in these values (P = 0.6171); however, significant differences were found between BioFire and GenMark (P = 0.0003) and between GenMark and Luminex (P = 0.0009). To investigate the source of the differences, assay disparities for each analyte or analyte group were analyzed . The three assays were equivalent for adenovirus, human metapneumovirus (MPV), influenza A, and RSV. BioFire had increased false-positive results for the endemic coronaviruses (CoVs) and so was found to be less accurate for that target group. The same was true for GenMark with influenza B and the parainfluenza viruses (PIVs). Rhinovirus/enterovirus presented an analytical challenge. The GenMark RVP assay reportedly does not detect enteroviruses; therefore, the 6 true-positive specimens for rhinovirus/enterovirus not detected by GenMark might have been enteroviruses and not false-negative results for rhinovirus.McNemar’s tests were performed to evaluate whether significant differences existed between any two of the assays. There was no significant difference in accuracy between BioFire and Luminex  and Chlamydia pneumoniae (BioFire and Luminex); however, because none of the samples tested was positive for either of these targets, they were not evaluated in this study.The BioFire and Luminex assays both include ch study , 13. OthOf the 24 samples that were consensus positive for two targets, 14 were dual positive by all three tests. Nine of the remaining 10 samples had one target that was positive by all three tests and one target for which one of the tests missed a single analyte. There were 3 GenMark false-negative samples (2 with rhinovirus/enterovirus and 1 with RSV), 3 Luminex false-negative samples , and 3 BioFire false-negative samples (1 with adenovirus and 2 with rhinovirus/enterovirus). The remaining discordant dual positive sample was CoV HKU1 positive by GenMark and BioFire and PIV-4 positive by GenMark. There were only 3 triple positive samples, 2 of which were concordant among the three tests. The remaining specimen was positive for adenovirus, PIV-4, and rhinovirus/enterovirus, but the BioFire assay was falsely negative for adenovirus and the Luminex assay was falsely negative for PIV-4.P value range of 0.831 to 0.997) or between age groups within each assay . When the analyses were repeated for NPA, a significant difference was found for patients ≤5 years of age (P = 0.0100), driven by the increased number of false-positive results with the GenMark RVP , which had a NPA of 55.0% in this age group. The intra-assay NPA for GenMark was not significant, with a P value of 0.0581; no other comparisons approached significance. The Luminex RPP was the only assay to achieve 100% NPA in the largest age group, i.e., 19 to 64 years of age.PPA was calculated for each assay in each age group . Chi-square analysis found no differences between the assays for any age group ; all 4 OC43 false-positive results were in conjunction with HKU1 true-positive results and so may be the product of known cross-reactivity between the two viruses in the BioFire assay (BioFire RP package insert). The only other false-positive result was for MPV. The assay detected 13/15 (86.7%) of the adenovirus-positive samples, 30/31 (96.8%) of the influenza A-positive samples, 14/15 (93.3%) of the influenza B-positive samples, and 32/34 (94.1%) of the RSV-positive samples. BioFire RP was 100% accurate for CoV NL63, PIV-2, PIV-3, and M. pneumoniae. The time from sample processing to result was ~67 min.The BioFire RP was the simplest assay to perform and the only sample-to-answer test in this study. The target menu incorporates the same viral panel as the GenMark RVP, with the addition of enterovirus. n = 4), rhinovirus (n = 10), PIV-1 (n = 2), PIV-2 (n = 3), PIV-4 (n = 4), and 1 each of adenovirus, MPV, OC43, and RSV. The GenMark assay was 100% accurate for CoV 229E, CoV HKU1, influenza A, and PIV-3. For a batch of 21 samples and associated controls, the time from sample processing to result was ~7.2 h.The GenMark RVP was the most labor-intensive assay, with an off-board extraction and two postamplification steps, i.e., exonuclease and hybridization-detection. The GenMark RVP offered the fewest targets but the highest overall PPA (97.3%). Of 7 false-negative results, 6 were for rhinovirus/enterovirus and thus could represent enterovirus-positive results, and 1 was for CoV NL63. This is somewhat tempered by the increased number of false-positive results, especially for patients ≤5 years of age. The overall NPA was 81.1%, as a result of false-positive results for influenza B (C. pneumoniae and M. pneumoniae). The relative ease of use was improved, compared to the initial Luminex xTAG RVP assay, which required separate extraction, amplification, exonuclease, secondary amplification, and hybridization steps. The Luminex NxTAG RPP assay still involves off-board extraction, but the eluate is added directly to lyophilized amplification and detection reagents, eliminating the need for making master mix or hybridization solution. Postamplification, the tray is transferred to the MagPix instrument for detection without additional manipulation. The RPP was the only one of the three tests evaluated with the capacity to detect human bocavirus. Fourteen NP swab samples tested positive for bocavirus; 11 were from patients 2 years of age or younger. All were submitted for confirmatory testing by bidirectional sequencing; 8 were confirmed as true-positive samples, 1 gave an indeterminate result, and 5 were negative.The Luminex RPP assay had the broadest selection of targets with 20, including bocavirus and two bacterial targets  version with SARS-CoV-2. The inclusion of SARS-CoV-2 in RPs is now essential, and it has also been added to the GenMark and BioFire RPs.Outcome studies have shown that multiplex respiratory pathogen testing can have positive impacts on patient care by decreasing the amount or duration of prescribed antibiotics, increasing the use of oseltamivir for influenza A-positive patients, reducing the time spent in isolation, and even reducing the overall lengths of stay for hospitalized children , 18. In There are now numerous FDA-cleared multiplex assays available for respiratory pathogen detection. We chose to focus on the three broadest panels. All three had high PPA and NPA values. The core menus of each panel are the same, with the exception of the lack of enterovirus and bacterial pathogens for the GenMark RVP. While the BioFire RP has the easiest workflow, the Luminex NxTAG RPP provides a compressed workflow with high throughput and similar performance characteristics, compared to BioFire RP and GenMark eSensor RVP.n = 350) from 329 symptomatic patients were used in this study; 19 patients had 2 specimens included and 1 patient had 3. For patients with more than 1 swab sample included, the average interval between swab collection dates was 47 days. Convenience sampling was used to enrich for positive specimens for each panel target. Patients fell into the following age groups: ≤5 years (n = 69), 6 to 18 years (n = 26), 19 to 64 years (n = 160), and ≥65 years (n = 74). Specimens were collected between January 2015 and July 2016, predominately between November 2015 and April 2016 (n = 325). Flocked swab samples were preserved in universal viral transport medium  and stored at −70°C until the time of study testing. Preservation of cellular nucleic acid during storage of eluted flocked swab samples has been shown previously  result was defined as being positive by two or more of the platforms or positive by the adenovirus LDT. All samples that were positive for bocavirus by Luminex and 1 sample with an unconfirmed M. pneumoniae result were analyzed with bidirectional sequencing using analytically validated primers that were directed against different genomic regions, compared with the Luminex assay primers. Where sequencing results were available, they were considered true results.The interpretation of results was performed according to the individual package inserts. The GenMark RVP was analyzed using the Research Use Only (RUO) software to include the P values of ≤0.05 were considered significant.All analyses were performed using GraphPad software . This study was approved by the University of North Carolina at Chapel Hill Institutional Review Board.


To evaluate the long-term clinical outcomes of degenerative lumbar scoliosis (DLS) with the administration of multisegment transforaminal lumbar interbody fusion (TLIF) combined with Ponte osteotomy long-level fixation fusion, as well as to identify the factors affecting health-related quality of life (HRQOL).This was a retrospective single-centre study involving comprehensive clinical data. The Oswestry Disability Index (ODI), visual analog scale (VAS) outcomes, and Scoliosis Research Society (SRS-22) questionnaire were recorded to assess HRQOL. A correlation analysis was performed to determine the association between HRQOL and radiographic parameters.A total of 41 consecutive patients  met the inclusion criteria with a follow-up of 8.62 ± 1.20 years. Factors associated with HRQOL were significantly improved post-operation. Global sagittal parameters, including the sagittal vertebral axis (SVA) and T1 pelvic angle (TPA), and local parameters, including apical vertebral translation (AVT) and apical vertebral rotation (AVR), were significantly improved at the last follow-up. Significantly strong correlations between each clinical and radiographic parameter were demonstrated. Moreover, a multiple linear regression analysis demonstrated that the differences in AVT and AVR were significantly correlated with the difference in lumbar lordosis (LL), which was significantly correlated with the differences in SVA and TPA.The surgical treatment of DLS with multisegment TLIF accompanied by Ponte osteotomy and long-level fixations improved the quality of life of patients with a long-term effect. AVR correction is an important factor for LL restoration that significantly correlates with improvements in the sagittal balance parameters SVA and TPA, which are key factors for guaranteeing good HRQOL. Degenerative lumbar scoliosis (DLS) is described as being a three-dimensional lumbar deformity that develops from the asymmetric degeneration of the facet joints and intervertebral discs . DLS is Given multiple chronic diseases, advanced age, and poor bone mass, DLS patients cannot endure major surgery. An increasing number of minimally invasive spine surgical procedures aimed at treating lumbar degenerative disease have gained public attention, such as oblique lateral interbody fusion (OLIF) and extreme lateral interbody fusion (XLIF) –8. MinimThus, in this study, we evaluated the long-term clinical outcomes of DLS with the administration of multisegment TLIF combined with Ponte osteotomy long-level fixation fusion and identified the factors affecting HRQOL. We further analyzed the associations among these factors to provide innovative insight into the surgical treatment of DLS.A retrospective study was conducted to evaluate the efficacy of multisegment TLIF combined with Ponte osteotomy long-level fixation/fusion in the surgical treatment of DLS. Our work followed the Declaration of Helsinki and was approved by the ethics committee of Xinqiao Hospital of Army Medical University.The inclusion criteria were as follows: age older than 50 years; degenerative lumbar or thoracolumbar scoliosis with a Cobb angle greater than 20° on anteroposterior (AP) radiographs; back and/or leg pain refractory to conservative treatment conducted for more than one year; patients having undergone surgery between July 2011 and July 2016; and a follow-up time more than five years. Patients were grouped according to SRS-Schwab and Roussouly classifications , 20. OpeThe exclusion criteria included adult idiopathic scoliosis, prior spinal trauma or fracture, spinal malignancy, spinal infection, and the presence of a previously implanted device.The patients were placed into a comfortable prone position. The lamina and articular process were revealed by using a middle incision followed by subperiosteal dissection, and pedicle screws were placed at predetermined levels. Symptomatic levels of neural compression were decompressed via the removal of the hypertrophic ligamentum flavum and facet joints. TLIF was performed at selected levels in the presence of disc herniation, lumbar stenosis, lateral listhesis or rotatory subluxation, and dynamic segmental instability. Additionally, TLIF was unilaterally performed for intervertebral release to maximize the mobility of the deformed segments. An interbody cage was inserted at the narrowest site of the asymmetric disc to restore the disc height Fig. . Ponte oThe recorded peri-operative parameters included the operative time, intra-operative blood loss, blood transfusion amount, and the number of fused vertebrae via TLIF, instrumented vertebrae, Ponte osteotomies, and decompression levels.The Oswestry Disability Index (ODI) and visual analog scale (VAS) were evaluated during the clinical assessment before surgery and at the last follow-up. Pre-operative and post-operative AP and lateral long-cassette radiographs were reviewed. Two physicians measured the films by using online Surgimap software , and the results were recorded as averages. The coronal Cobb angle, apical vertebral translation (AVT), and coronal balance parameters, such as C7-CSVL, were measured in the coronal plane. The apical vertebral rotation (AVR) was measured by using Nash-Moe grades as a transverse plane parameter. The LL, L1-S1 length , and sagittal balance parameters, including the sagittal vertebral axis (SVA), pelvic incidence (PI), sacral slope (SS), pelvic tilt (PT), and T1 pelvic angle (TPA), were measured in the sagittal plane.t tests or Mann–Whitney U tests. The relationships between the differences in functional outcomes and radiographic parameters were evaluated by using the Spearman correlation analysis. A linear regression analysis was used to assess the factors related to the clinical and radiographic outcomes (in a stepwise manner). All of the statistical results were considered to be statistically significant if p < 0.05. The statistical analysis was performed with the SPSS 24.0 software package.Comparisons of the functional outcomes and radiographic parameters before surgery and at the last follow-up evaluation were performed by using paired A total of 41 patients were included (15 men and 26 women), with a mean age of 63.0 ± 8.2 years (range: 50–78 years) and a follow-up time of 8.62 ± 1.20 years (range: approximately 5.11–10.83 years). All of the patients presented with back pain, 30 patients presented with radiculopathy, and 22 patients presented with claudication. Twenty-eight of 41 (68.3%) patients had two or more medical comorbidities, including osteoporosis (26/41), diabetes mellitus (15/41), and hypertension (14/41). To maintain the balance of the spine, the upper instrumented vertebrae were mainly located at T7-T10/T11-L2 (22/19), and the lower instrumented vertebrae were located at L5/S1 (5/16). On average, the number of TLIFs was 2.66 ± 0.69 (approximately 2–4), and the number of Ponte osteotomy procedures was 3.76 ± 0.89 (approximately 2–6). To relieve the nerve, 2.07 ± 0.82 (approximately 1–4) segments were decompressed. The mean operative time was 239.68 ± 59.44 (approximately 155–390) min, with an average blood loss of 738.75 ± 74.93  ml, and the mean post-operative hospital stay was 8.38 ± 2.45 days (approximately 5–13).p = 0.152), but little statistical significant improvement in quality of life  at the last follow-up. The long-term improvement of radiographic data was not statistically significant .The distribution of patients according to Roussouly and SRS-Schwab classification is shown in Table The incidence of early complications was 14.6%, including gastrointestinal dysfunction (4/41), superficial wound infection (1/41), and urinary tract infection (1/41). All of the complications were handled well with drug treatment. The morbidity of the late complications was 9.8%. One patient experienced screw loosening with sagittal imbalance, and one patient had an osteoporotic vertebral compression fracture. Both patients underwent revision surgery and had a good outcome during the follow-up. Two patients presented with coronal imbalance and were handled well via nonsurgical procedures.A correlation analysis was performed for all of the clinical and radiographic parameters, as listed in Table The ideal surgical treatment for DLS is a consistently important topic worthy of in-depth study and has resulted in intense discussion , 4. MultSeveral studies have reported a correlation between the clinical outcomes of DLS surgery and the restoration of LL. For example, Iizuka et al.  reportedPonte osteotomy, which involves the wide resection of facet joints, as well as of the laminae and ligamentum flavum, has been widely used to correct kyphosis by shortening the posterior spinal column and could provide flexibility in flexion, extension, and rotation for maximizing coronal, sagittal, and rotational corrections , 14. PonThe SRS-Schwab system has been widely recognized as being a reliable algorithm aiding in operative planning, and modifier parameters have been shown to correlate with the postoperative HROOL of degenerative scoliosis , 36. HowIn this study, the selected multisegment TLIF procedures were performed at the symptomatic and spinal stenosis levels, in which multilevel Ponte osteotomy released the posterior column via inferior and superior facet joint removal, and convex facet space was compressed to restore lordosis. The combination procedure produced adequate spinal decompression and deformity corrections with less bone and blood loss and little interference with the nerves; additionally, it restored the height of the anterior column and LL. In our group, the improvements in either SRS-Schwab classification or Roussouly types were clearly evident Fig. . DLS patThere are currently no significant consensus complication rates. Cho et al.  reportedThere were several limitations to our study. We did not analyze the relationship between radiographic parameters and functional outcomes, and the risk factors for complications were not determined due to the limited sample size. Further biomechanical studies are required to confirm the stability of fusion constructs. Moreover, the relatively small sample size may have caused a selection bias, and a larger cohort is needed to address these limitations.Surgical treatment of DLS with multisegment TLIF accompanied by Ponte osteotomy and long-level fixations improved the quality of life of patients with a long-term effect. This combination treatment targeting stenosis, instability, and ridged deformity is coupled with few complications. AVR correction is an important factor for LL restoration that significantly correlates with improvements in the sagittal balance parameters SVA and TPA, which are key factors to guarantee good HRQOL.


Zea mays) growth performance has been hindered due to the high soil salinity. Salinity is one of the most severe abiotic stresses that has led to growth imbalance and profitability of harvests in arid and semi-arid regions. Plants have taken advantage of salt-tolerant bacteria as plant growth-promoters to enhance growth and reduce the adverse effects of salinity through the regulation of some biochemical, physiological, and molecular features. Preferences for non-chemical, eco-friendly, and economical approaches have caused the inquiry of the Bacillus genus as a joint group of plant growth-promoting rhizobacteria known to alleviate salt-stress impacts. In the present study, halotolerant Bacillus strains were isolated from salt-marshland soil and characterized for their physiological, molecular, and biochemical properties. Twenty-four bacterial isolates collected from high saline fields of salt marshland were analyzed by MALDI-TOF MS proteome analysis, which confirmed the taxonomic affiliation with Bacillus cereus, Bacillus subtilis, Bacillus atrophaeus, and Bacillus thorngiensis. Applying the isolates on maize plants as bio-inoculant bacteria obviously increased the growth parameters (P < 0.01). Pot experiments showed that isolates 74 and 90 were the most prominent strains to minimize the harmful effects of salinity. Its effects are heightening the potassium/sodium ratio and K-Na selectivity in shoots and roots measured by flame atomic absorption photometry (AAS). Accordingly, Bacillus cereus isolate 74 showed a maximum increase in dry weights of the shoot (133.89%), root (237.08%), length of the shoot (125%), and root (119.44%) compared to the control condition. Our findings suggest that bacteria isolated from marshland may be an economical and simple means to increase plant growth and resistance to high salinity soil conditions.Maize ( Soil salinization is a widespread threat to agriculture and rangeland productivity in Iran. Salt marshes are extremely biodiverse habitats with complex structures  which plArthrobacter, Bacillus, and Pseudomonas species such as Bacillus pumilus, B. aquimaris, B. arsenicus, B. sporothermodurances, Arthrobacter sp., B. cereus, B. subtilis, and P. medicona from salt-affected rhizosphere significantly improved wheat growth by indole-3-acetic acid (IAA), siderophore and gibberellin production as well as phosphorus solubilization [Achromobacter piechaudii ARV8 [Stenotrophomonas rhizophila strain DSM14405T [Azospirillum strains [Bacillus cereus [Halobacillus sp. and Bacillus halodenitrificans [Pseudomonas syringae and Pseudomonas fluorescens [Zhihengliuella halotolerans, Staphylococcus succinus, Bacillus gibsonii, Oceanobacillus oncorhynchi, Halomonas sp., and Thalassobacillus sp. [Rhodococcus, Oceanospirillales, Bacillales, Actinomycetales [Leclercia adecarboxylata [Bacillus, as a predominant bacterial genus under a stressed environment, is powered by an external shield of the formidable cell wall [The salt-tolerant plant growth-promoting rhizobacteria (PGPR) isolated from the saline condition can be used as probiotics for saline soil agriculture, which can be a promising substitute for improving crop yield approaches . As freqlization . Beneficdii ARV8 , StenotrSM14405T , Azospir strains , Bacillus cereus , Halobacorescens , Zhihengllus sp. , severalycetales . Leclercboxylata  on diffeell wall , endospoell wall , stable ell wall , and intell wall  to cope The present study aimed to isolate and characterize bacterial isolates collected from soil samples taken from one of the desert salt marshes in Iran. The potential of the bacterial isolates was assessed to promote maize growth parameters under salinity stress.o14’13.92“ E and latitude 34o54’7.20” N). Eight soil samples were collected from 10 to 20 cm of the soil surface and completely mixed together and finally; one soil sample was transferred to the laboratory. The soil sample was dried in the dark and at room temperature for at least two days before sieving. Following the drying process, the soil sample was sieved through a 2 mm sieve to remove pebbles and other inert material and then kept in a zip lock cover.Soil samples were collected from a desert marshland located at the north eastern of Qom (longitude 51+ MnSO4), LB, Moller Hinton Agar (MHA), Acidithiobacillus (APH) medium, Violet Red Bile Lactose (VRB) agar medium, GYM Streptomyces medium, DPM medium, Azospirillum medium, and Azotobacter medium, were used. All media were sterilized at 121 °C for 20 min and plates were incubated inside polyethylene bags at 4 °C. For isolation of bacteria, 1 g of soil sample was suspended in 2 ml of sterile physiological saline (0.9% w/v NaCl) and then vortexed for 1 min. After sedimentation of soil particles, 100 ul of the supernatant was used for serial dilutions in the range of 10−1–10−7. Each dilution level was prepared in triplicate. Ten microliters of each dilution level were applied on the surface of solidified media by glass spreaders and incubated in an inverted position at 30 °C in the absence of light for 1–3 days. All instruments were sterilized completely before use and all dilution procedures were performed inside a laminar flow clean bench to achieve strict asepsis. Colonies were isolated based on the morphological characteristics , and diameter) using sterile toothpicks after two days of incubation at 30 °C. Accordingly, the number of each isolate was stated in colony-forming units per 1 g of soil (CFU g−1). Individual colonies were transferred and streaked separately on the same fresh media. Each plate was re-streaked twice to ensure strains purity and also cultured on the same liquid media for cryo-stock preparation. Long-term storage was carried out on a liquid medium containing 25% v/v glycerol at −70 °C.Eleven culture media, including Nutrient Agar (NA), Nutrient Agar plus MnSO4 (NAGram staining of bacteria was examined after 48 h of incubation on MHA following the method of Bartholomew . A non-sThe growth of isolates (expressed as CFU) was evaluated in dark and under cold, drought, salinity, heat, and alkalinity stresses. Muller Hinton media was considered a basal growth media for all experiments. For cold and heat stresses, isolates were cultured at 15 and 60 °C for 10 hours, respectively. Basal media containing 100 mM NaCl, 25% PEG6000, and pH = 10 were prepared for salinity, drought, and alkalinity stresses and incubated for 10 h at 30 °C, respectively.Isolates were sub-cultured twice on MHA at 30 °C for 24 h. Then approximately 100 μg of the bacterial colony were directly transferred to the MALDI target spot. Followed by drying at room temperature and overloading with 1uL of matrix solution (10 mg/ml a-cyano-4-hydroxycinnamic acid in 50% acetonitrile and 2.5% trifluoroacetic acid), each measurement was performed in two replications. MS analysis was carried out on an Autoflex MALDI-TOF mass spectrometer using Flex Control 3.4 software . Soil isolates with a valid MALDI-TOF MS score of 2 were undoubtedly assigned to the genus/species level.The bacterial classification was carried out using BioTyper 3.1 software . All identifications were reported with the following score values; unreliable identification was <1.7, 1.7–2.0 considered a possible genus identification and 2.0–2.3 expressed as a secure genus identification and probable species identification; and finally, >2.3 was regarded as highly probable species identification. Only the highest score value of all mass spectra belonging to individual cultures  was recorded .Zea mays. Var Kosha) were obtained from Seed and Plant Improvement Institute of Karaj , soaked in distilled water for 24 h and left to germinate. For the first irrigation, the sterilized MHA was treated with two salinity levels (0 and 100 mM NaCl) and bacterial isolates (CFU 2 × 103) and used as irrigation water. Each treatment consisted of one bacterial isolate and one salinity level. After the first irrigation, a daily plant watering (5 ml/ per day) was carried out using sterilized pure water. A completely randomized block design with factorial treatments in three replications was employed for the experiment. After 20 days, plants were harvested, and shoot and root length (cm) and shoot and root fresh weight (mg) were successively recorded. For dry weight, samples were dried at 50 °C and measured after reaching a stable weight. Whole dry weight (mg), whole length (cm), and Shoot/Root were calculated. Sodium and potassium contents were extracted as described by Sakr et al., [Maize seeds  to check the level of association between control/salinity stress and relative growth of soil isolates. Cluster analysis was done based on the Tomida report [All statistical analyses were performed by R software (version 3.6.2). The significance of the experiment was tested by one-way analysis of variance (ANOVA) and means separation was performed using Fisher’s protected Least Significant Difference (LSD) test at a report  using CL+, 3 on LB, 2 on VRB, 3 on AZTO, and 4 on GYM through the morphological distinctions. All isolates presented a rode shape in cell form with mostly smooth and flat surface colony shape except for two isolates (35 and 120) by screening them on selective media. The isolates came in a variety of colors, including cream, white, yellow, orange, brick red, and red. Table +, LB, VRB, AZTO, and GYM).Of 24 isolates, seven isolates were obtained on MHA, 2 on NA, 3 on NAs 35 and 20 by scrTable Bacillus genus. Protem analysis of the isolates produced an exact match to four species during MALDI-TOF and the results showed all the isolates belonged to B.cereus, B atrophaeus, B.subtilis, and B.thuringiensis. Besides, the results of biochemical tests and Gram staining confirmed the results of MALDI-TOF. In this way, all isolates were circular, Gram-positive, and produced endospores; so, they were also characterized based on distinguishing features.Molecular characterization and biochemical analysis were done on bacterial isolates with catalase, KOH degradation, and oxidase abilities. All 24 isolates were shown Gram-positive and minus catalase reactions. However, there were differences between the isolates for oxidase and KOH degradation tests. In this regard, only four isolates showed KOH digestion activity  and six isolates did not show oxidase activity . Table The results of the application of isolates on plants indicated that yield per plant and growth parameters were significantly boosted by bacterial inoculation under salinity stress conditions; so isolates could alleviate the deleterious impacts of salinity on the growth of maize plants under natural salinity field conditions. Shoot dry weight, root dry weight, shoot length, and root length readings in maize leaves and roots were significantly increased by bacterial isolates under salinity stress. Hence, bacterial assessments improved the growth parameters of maize plants compared with the non-inoculated control also under salinity stress.p < 0.001). Four growth parameters were associated with salt tolerance analysis in maize and the analyses were linked to shoot dry weight, root dry weight, shoot length, and root length of maize plants under normal and salinity conditions. Table The results of tests under salinity conditions showed distinct differences in the shoot and root growth between isolates’ treatments. Plant-microbe interactions under salinity stress were statistically significant  increased shoot dry weight and root dry weight, which are useful measures of the physiological stability of plants. The exploitation of soil microbes for utilizing salt-stressed land is a useful method that may provide a quick-fix solution to salinity [Bacillus genus have been widely reported as promising candidates for bacterization because of their ability to eliminate or alleviate the harmful effects of saline stress, regulate plant physiological characteristics, and promote plant growth [B. megaterium.The findings of the present study revealed that shoot, root dry weight per plant, and length of shoot and root were significantly increased by bacterial applications under salinity stress conditions. Inoculation of isolates significantly  plays a crucial role in water stress tolerance in salinity stress. It is an osmotically active compound that contributes to water absorption in the root [Zea mays [In summary, the findings of the current study suggest that bacterial isolates belonging to  quality . Based othe root , 20. AbdIndeed, salt marsh sediment bacteria remain primarily in a black box regarding their diversity and functional roles through salt marsh benthic food web pathways . TherefoZ. mays plants with beneficial soil bacterial isolates have a great impact on plant growth and their persistence over abiotic stresses such as salinity. It is important to find practical approaches to isolate and characterize such bacteria. One of the most critical steps is how to figure out the correct place to isolate these bacteria. The particular conditions of salt marshlands can provide a unique environment for the emergence of salt-resistant bacteria. Many of these kinds of isolates, as well as resisting salt stress, may create resistance in surrounding organisms. The main challenge in this study was to survey the effectiveness of isolates on plant growth and their salt resistance. Our findings indicate that B. subtilis 73, B. cereus 74, and B. atrophaeus 90 are talented salt-marshland strains that need to be more analyzed in further studies for their application feasibility on the maize crop.Assessing