Defining Age-Adjusted PI-LL Targets for Surgical Realignment in Adult Degenerative Scoliosis: A Retrospective Cohort Study.

Objectives: The purpose of this study was to investigate postoperative pelvic incidence minus lumbar lordosis mismatch (PI-LL) and health-related quality of life (HRQOL) outcomes to determine age-adjusted PI-LL targets. Method: The dataset encompassed a range of variables, including age, sex, body mass index, Charlson comorbidity index, presence of osteopenia, hospital stay, operative duration, blood loss, American Society of Anesthesiologists score, number of fusion levels, lumbar lordosis, sagittal vertical axis, pelvic incidence, and PI-LL. The non-linear relationship between PI-LL and clinical outcomes was examined using a curve analysis, with adjustments made for potential confounding variables. Upon identification of a non-linear relationship, a two-piecewise regression model was employed to determine the threshold effect. Results: A total of 280 patients were enrolled. In the fully adjusted model, the optimal PI-LL target for patients aged 45-54 years old was PI-LL < 10°, the optimal target for patients aged 55-74 was 10-20°, and the optimal target for patients older than 75 years was more suitable for PI-LL > 20°. In the curve-fitting graph, it could be seen that the relationship between PI-LL and HRQOL outcomes was not linear in each age group. The peaks of the curves within each group occurred at different locations. Higher and lower thresholds for optimal surgical goals were determined using the two-piecewise regression model from the SRS-22 score and the ODI score. Conclusions: This study showed that the optimal PI-LL after corrective surgery in adult degenerative scoliosis patients should be adjusted according to age.

Artificial intelligence in skeletal metastasis imaging.

In the field of metastatic skeletal oncology imaging, the role of artificial intelligence (AI) is becoming more prominent. Bone metastasis typically indicates the terminal stage of various malignant neoplasms. Once identified, it necessitates a comprehensive revision of the initial treatment regime, and palliative care is often the only resort. Given the gravity of the condition, the diagnosis of bone metastasis should be approached with utmost caution. AI techniques are being evaluated for their efficacy in a range of tasks within medical imaging, including object detection, disease classification, region segmentation, and prognosis prediction in medical imaging. These methods offer a standardized solution to the frequently subjective challenge of image interpretation.This subjectivity is most desirable in bone metastasis imaging. This review describes the basic imaging modalities of bone metastasis imaging, along with the recent developments and current applications of AI in the respective imaging studies. These concrete examples emphasize the importance of using computer-aided systems in the clinical setting. The review culminates with an examination of the current limitations and prospects of AI in the realm of bone metastasis imaging. To establish the credibility of AI in this domain, further research efforts are required to enhance the reproducibility and attain robust level of empirical support.

Co-Effects of Nitrogen Fertilizer and Straw-Decomposing Microbial Inoculant on Decomposition and Transformation of Field Composted Wheat Straw.

Although straw is an abundant and useful agricultural byproduct, it, however, exhibits hardly any decomposition and transformation. Despite the successful application of chemical and biological substrates for accelerating straw decomposition, the co-effects and mechanisms involved are still unknown. Herein, we performed a 120 day field trial to examine the co-effects of a nitrogen fertilizer (N) and a straw-decomposing microbial inoculant (SDMI) on the straw mass, nutrient release, and the straw chemical structure of composted wheat straw in the Chaohu Lake area, East China. For this purpose, four treatments were selected with straw: S (straw only), NS (N + straw), MS (SDMI + straw), and NMS (N + SDMI + straw). Our results indicated that NMS caused a higher straw decomposition rate than S, NS, and MS (p < 0.05) after 120 days of composting. The N, P, and K discharge rates in treating with NMS were higher than other the treatments at 120 days. The A/OA ratios of the straw residues were gradually increased during the composting, but the treatment of NMS and MS was lower than the CK at the latter stage. The RDA showed that the decomposition rate, nutrient release, and the chemical structure change in the straw were cumulative, while respiration was strongly correlated with lignin peroxidase, manganese peroxidase, and neutral xylanase. In conclusion, nitrogen fertilizer or straw-decomposing microbial inoculant application can improve the decomposition rate and nutrient release with oxidase activity intensified. However, the co-application of nitrogen fertilizer and a straw-decomposing microbial inoculant promoted straw decomposition and enzyme activity better than a single application and showed a lower decomposition degree, which means more potential for further decomposing after 120 days.

C1 triangular Coons surface construction and image interpolation based on new Side-Side and Side-Vertex interpolation operators.

In this paper, a new class of rational quadratic/linear trigonometric Hermite functions with two shape parameters is proposed. Based on these Hermite functions, new improved first class of Side-Side (FCSS), second class of Side-Side (SCSS), first class of Side-Vertex (FCSV) and second class of Side-Vertex (SCSV) interpolation operators are proposed respectively, which can be used to construct C1 Coons surfaces over triangular domain. By altering the values of two shape parameters, the shape of the Coons surface patch can be adjusted flexibly, but without affecting the function values and partial derivatives of the boundaries. For constructing the triangular surface patches with the center of mass passing through a fixed point, we also give a center of mass function value control method, by which we can solve the corresponding shape parameter values. Moreover, we also apply these four improved interpolation operators to image interpolation. Compared with some widely used image interpolation methods, our methods achieve competitive performance.

Linking chemical structure of dissolved organic carbon and microbial community composition with submergence-induced soil organic carbon mineralization.

Much research has been devoted to investigating how water-extractable organic carbon (DOC) concentration and microbial activity regulate soil organic carbon (SOC) mineralization when soils are saturated with water. However, the relationships of DOC chemical structure and microbial community composition with SOC mineralization, as well as the relative contributions of microbial decomposers and their substrates on the mineralization rate have rarely been examined. In a laboratory experiment, we incubated two typical cropland soils (an Entisol and a Mollisol) of China for 360 days under submerged and non-submerged conditions, and we evaluated the concentration and chemical structure of soil DOC, soil microbial metabolic potential and community composition by using total C/N analysis, solution-state 1H NMR, Biolog EcoPlates, and 16S rRNA amplicon sequencing, respectively. The results showed that submergence significantly increased DOC concentration (P < 0.01) and microbial activity (P < 0.001) and changed DOC chemical structure in the Entisol (P < 0.01). In the Mollisol, it significantly increased the rate (P < 0.01) and cumulative extent (P < 0.001) of SOC mineralization and DOC concentration (P < 0.01) as well as altering the composition of the microbial community (P < 0.001). Moreover, the SOC mineralization rate was better explained by microbial community composition (Entisol: SPC = -0.71, P < 0.001; Mollisol: SPC = 0.92, P < 0.001) than by DOC concentration (Entisol: SPC = 0.21, P > 0.05; Mollisol: SPC = 0.30, P < 0.05) or DOC chemical structure (Entisol: SPC = 0.12, P > 0.05; Mollisol: SPC = -0.45, P < 0.001). Our study revealed that the bacterial community composition had a close relationship to the rate of submergence-induced SOC mineralization in both soils, but only DOC concentration and chemical structure were effective predictors of mineralization rate in the low-pH Mollisol.

[Value of blood apoH gene expression and urinary NAG and RBP in early diagnosis of renal function damage in neonates].

OBJECTIVE: To study the value of apolipoprotein H (apoH) gene expression in peripheral blood mononuclear cell (PBMC) and urinary N-Acetyl-beta-D-Glucosaminidase (NAG) and retinal-binding protein (RBP) in the early diagnosis of renal function damage in neonates. METHODS: Sixty sick neonates who renal function damage probably occurred were enrolled. The blood and urinary samples were collected twice within 48 hrs following admission, with an interval of 12-24 hrs. Expression of apoH gene in PBMC was determined with RT-PCR. The levels of blood urea nitrogen (BUN) and creatinine, and urinary activities of NAG and RBP were measured with enzymatic reaction. RESULTS: The abnormal rates of blood apoH and urinary NAG and RBP were 73.3%, 83.3% and 76.7%, respectively in the first detection. The second detection for blood apoH and urinary NAG and RBP showed abnormal rates of 70.0%, 66.7% and 76.7%, respectively. There were no significant differences in the abnormal rates between the three markers either in the first or the second detection (P>0.05). Beside there were no significant significances in the abnormal rates between urinary NAG and blood BUN in the second detection, the abnormal rates of blood apoH and urinary NAG and RBP in both detections were significantly higher than those of BUN or creatinine (P<0.01 or 0.05). CONCLUSIONS: There are identical values of blood apoH gene expression and urinary NAG and RBP in the early diagnosis of renal function damage in neonates. The above three markers are more sensitive to early renal function damage than blood BUN and creatinine.

[Clinical significance of dynamic pressure-volume curve in neonatal mechanical ventilation].

OBJECTIVE: To study the characteristics and role of dynamic pressure-volume curve (P-V curve) in neonatal mechanical ventilation. METHODS: A dynamic P-V curve was automatically drawn by the Stephanie ventilator. The slope rate of dynamic P-V curve was measured in 25 neonates who received mechanical ventilation 1, 24, 48 and 72 hrs after ventilation and before weaning from ventilation. Minute-ventilation (MV), mean airway pressure (Pmean), and fraction of inspired oxygen (FiO2) were recorded. The patterns of dynamic P-V curve during abnormal ventilation (resistance to ventilator, part or complete airway obstruction, airway leaking and tracheal catheter exodus) were observed. RESULTS: With the improvement of pulmonary disease, the slope rate of P-V curve and MV increased, Pmean and FiO2 decreased, and the P-V curve shifted to the volume axle. The slope rate of curve 48 and 72 hrs after ventilation and before weaning from ventilation (1.05+/-0.48, 1.10+/-0.42 and 1.13+/-0.37 mL/cmH2O respectively) increased significantly compared with that 1 hr after ventilation (0.76+/-0.53 mL/cmH2O) (p<0.05 or 0.01). Abnormal ventilation led to abnormal appearance of dynamic P-V curve. CONCLUSIONS: The increasing slope rate of dynamic P-V curve and the curve shifting to volume axle in neonatal mechanical ventilation may be associated with the improvement of pulmonary disease. The appearance changes of the curve may be of value in the assessment of abnormal ventilation.