Nomogram Development and Validation for Predicting Postoperative Recurrent Lumbar Disc Herniation Based on Paraspinal Muscle Parameters.

Purpose: Previous studies highlight paraspinal muscles' significance in spinal stability. This study aims to assess paraspinal muscle predictiveness for postoperative recurrent lumbar disc herniation (PRLDH) after lumbar disc herniation patients undergo percutaneous endoscopic transforaminal discectomy (PETD). Patients and Methods: Retrospectively collected data from 232 patients undergoing PETD treatment at our institution between January 2020 and January 2023, randomly allocated into training (60%) and validation (40%) groups. Utilizing Lasso regression and multivariable logistic regression, independent risk factors were identified in the training set to construct a Nomogram model. Internal validation employed Enhanced Bootstrap, with Area Under the ROC Curve (AUC) assessing accuracy. Calibration was evaluated through calibration curves and the Hosmer-Lemeshow goodness-of-fit test. Decision curve analysis (DCA) and clinical impact curve (CIC) were employed for clinical utility analysis. Results: Diabetes, Modic changes, and ipsilesional multifidus muscle skeletal muscle index (SMI) were independent predictive factors for PRLDH following PETD (P<0.05). Developed Nomogram model based on selected predictors, uploaded to a web page. AUC for training: 0.921 (95% CI 0.872-0.970), validation: 0.900 (95% CI 0.828-0.972), respectively. The Hosmer-Lemeshow test yielded χ 2=5.638/6.259, P=0.688/0.618, and calibration curves exhibited good fit between observed and predicted values. DCA and CIC demonstrate clinical net benefit for both models at risk thresholds of 0.02-1.00 and 0.02-0.80. Conclusion: The Nomogram predictive model developed based on paraspinal muscle parameters in this study demonstrates excellent predictive capability and aids in personalized risk assessment for PRLDH following PETD.

Fighting against Clostridioides difficile infection: Current medications.

Clostridioides difficile (formerly Clostridium difficile) has been regarded as an 'urgent threat' and a significant global health problem, as life-threatening diarrhoea and refractory recurrence are common in patients with C. difficile infection (CDI). Unfortunately, the available anti-CDI drugs are limited. Recent guidelines recommend fidaxomicin and vancomycin as first-line drugs to treat CDI, bezlotoxumab to prevent recurrence, and faecal microbiota transplantation for rescue treatment. Currently, researchers are investigating therapeutic antibacterial drugs (e.g. teicoplanin, ridinilazole, ibezapolstat, surotomycin, cadazolid, and LFF571), preventive medications against recurrence (e.g. Rebyota, Vowst, VP20621, VE303, RBX7455, and MET-2), primary prevention strategies (e.g. vaccine, ribaxamase, and DAV132) and other anti-CDI medications in the preclinical stage (e.g. Raja 42, Myxopyronin B, and bacteriophage). This narrative review summarises current medications, including newly marketed drugs and products in development against CDI, to help clinicians treat CDI appropriately and to call for more research on innovation.

Paraspinal muscle parameters' predictive value for new vertebral compression fractures post-vertebral augmentation: Nomogram development and validation.

Objective: Prior research underscores the significance of paraspinal muscles in maintaining spinal stability. This study aims to investigate the predictive value of paraspinal muscle parameters for the occurrence of new vertebral compression fractures (NVCF) following percutaneous vertebroplasty (PVP) or percutaneous kyphoplasty (PKP) in patients with osteoporotic vertebral compression fractures (OVCF). Methods: Retrospectively collected data from October 2019 to February 2021 (internal validation, n = 235) and March 2021 to November 2021 (external validation, n = 105) for patients with OVCF treated with PVP/PKP at our institution. They were randomly divided into training (188 cases) and validation groups (47 cases) at an 8:2 ratio. Lasso regression and multivariable logistic regression identified independent risk factors in the training set, and a Nomogram model was developed. Accuracy was assessed using receiver operating characteristic curves (ROC), calibration was evaluated with calibration curves and the Hosmer-Lemeshow test, and clinical utility was analyzed using decision curve analysis (DCA) and clinical impact curve (CIC). Results: Surgical approach, spinal computed tomography (CT) values, and multifidus skeletal muscle index (SMI) are independent predictors of postoperative NVCF in OVCF patients. A Nomogram model, based on the identified predictors, was developed and uploaded online. Internal validation results showed area under the curve (AUC) values of 0.801, 0.664, and 0.832 for the training set, validation set, and external validation, respectively. Hosmer-Lemeshow goodness-of-fit tests (χ2 = 7.311-14.474, p = 0.070-0.504) and calibration curves indicated good consistency between observed and predicted values. DCA and CIC demonstrated clinical net benefit within risk thresholds of 0.06-0.84, 0.12-0.23, and 0.01-0.27. At specificity 1.00-0.80, the partial AUC (0.106) exceeded that at sensitivity 1.00-0.80 (0.062). Conclusion: Compared to the spinal CT value, the multifidus SMI has certain potential in predicting the occurrence of NVCF. Additionally, the Nomogram model of this study has a greater negative predictive value.

Investigating the regional ecological environment stability and its feedback effect on interference using a novel vegetation resilience assessment model.

Vegetation resilience is critical for understanding the dynamic feedback effect of regional ecological environment stability against interferences. Thus, based on quantify the interferences of climate dryness and vegetation water deficit affecting vegetation growth function, incorporate mechanical Hooke's law to develop a vegetation resilience assessment model by quantitatively expressing vegetation growth function maintenance ability, to reveal the ecological environment stability and its feedback effect on interferences in the study area. The essential discoveries of the study are as follows: (1) with the increase of precipitation and the improvement of afforestation on soil erosion, the interferences intensity of climate dryness and vegetation water deficit in the ecological environment decreased by 5.88 % and 4.92 % respectively, the regional vegetation growth function loss was improved, especially in the southern region; (2) the decrease of vegetation growth function loss promoted the vegetation resilience level fluctuated from class II to class IV, with the average annual vegetation resilience increased by 7.02 %, reflecting that the regional ecological environment stability increased from difficult to rapid recovery after disturbance, and the benefit was especially noticeable in the eastern and southern forested areas; (3) the contribution rates of climate dryness and vegetation water deficit to the variation of vegetation resilience caused by vegetation restoration were -1.38 % and 4.73 %, respectively, and the prominent positive feedback effect of increasing vegetation resilience with decreasing vegetation water deficit degree in forest restoration area, indicating that the vegetation water deficit greatly impacts ecological environment stability in the study area, and forest restoration constantly improves regional ecological environment stability more than grassland restoration. This research has crucial guiding implications for supporting the sustainable development of regional ecological environments.

Serum metabolomic profiling of patients with liver cirrhosis at different stages.

An accurate and non-invasive diagnosis of the clinical stage is critical for effectively managing liver cirrhosis. This study aimed to identify serum metabolite biomarkers and clinical features that may reliably predict high-risk cirrhosis. This cross-sectional study recruited 94 cirrhotic patients (70 for identification cohort, 24 for validation cohort) from Minhang Hospital Affiliated with Fudan University between 2018 and 2021, who were analyzed by targeted quantitative metabolomics technique. Baseline clinical characteristics were collected, and different stage cirrhosis classification was performed according to the presence or absence of decompensated events. Potential metabolite biomarkers were screened, and a model for predicting the decompensation stage was created. Finally, the incidence of decompensated outcomes was analyzed. A total of 560 metabolites were detected in the identification cohort. Indole-3-propionic acid (IPA) was the most significantly decreased metabolic biomarker in the decompensated group (P<0.01, |log2FC| >2), having the strongest correlation with hyaluronic acid (r=-0.50, P<0.01). It also performed well for differentiating decompensated cirrhosis with an area under the curve (AUC) of 0.79(0.75 at internal validation). Another diagnostic model consisting of indole-3-propionic acid, hemoglobin, and albumin showed better predictive performance with an AUC of 0.97 (0.91 at internal validation). Also, 31 (44.29%) patients developed decompensated events at a median follow-up of 22.76±15.24 months. The cumulative incidence of decompensated events based on IPA subgroups (IPA <39.67ng/ml and ≥39.67ng/ml) showed a significant difference (P<0.01). "Indole-3-propionic acid" and a diagnostic model of hemoglobin and albumin can non-invasively identify cirrhotic populations at risk for decompensation, aiding in future management of liver cirrhosis.

Safety and efficacy of phage application in bacterial decolonisation: a systematic review.

Colonisation by bacterial pathogens typically precedes invasive infection and seeds transmission. Thus, effective decolonisation strategies are urgently needed. The literature reports attempts to use phages for decolonisation. To assess the in-vivo efficacy and safety of phages for bacterial decolonisation, we performed a systematic review by identifying relevant studies to assess the in-vivo efficacy and safety of phages for bacterial decolonisation. We searched PubMed, Embase (Ovid), MEDLINE (Ovid), Web of Science, and the Cochrane Library to identify relevant articles published between Jan 1, 1990, and May 12, 2023, without language restrictions. We included studies that assessed the efficacy of phage for bacterial decolonisation in humans or vertebrate animal models. This systematic review is registered with PROSPERO, CRD42023457637. We identified 6694 articles, of which 56 (51 animal studies and five clinical reports) met the predetermined selection criteria and were included in the final analysis. The gastrointestinal tract (n=49, 88%) was the most studied bacterial colonisation site, and other sites were central venous catheters, lung, nose, skin, and urinary tract. Of the 56 included studies, the bacterial load at the colonisation site was reported to decrease significantly in 45 (80%) studies, but only five described eradication of the target bacteria. 15 studies reported the safety of phages for decolonisation. No obvious adverse events were reported in both the short-term and long-term observation period. Given the increasing life-threatening risks posed by bacteria that are difficult to treat, phages could be an alternative option for bacterial decolonisation, although further optimisation is required before their application to meet clinical needs.

Diagnostic Potential of microRNA-122 for Stage Classification in Patients with HBV-Related Cirrhosis.

Objective: Previous studies have suggested that microRNA-122 has a relatively high diagnostic value for chronic viral hepatitis detection. In this study, we evaluated the diagnostic value of serum microRNA-122 in different stages of HBV-related cirrhosis，and serum microRNA-122 may serve as a potential biomarker for staging HBV related cirrhosis patients.. Methods: A total of 80 patients with HBV-related cirrhosis were included. Patients were characterized according to Child-Pugh score, laboratory parameters, and complications, and divided into compensated cirrhosis group and decompensated cirrhosis group. Wherein, the compensatory group for liver cirrhosis includes 21 patients, the compensatory group has 59 patients. Blood was collected from all patients, and RT-qPCR analyzed the expression levels of microRNA-122. Results: Serum microRNA-122 was decreased, while Child-Pugh score, Meld score, Prothrombin time, total bilirubin, and Direct bilirubin were higher in a decompensated group compared to the compensated group (all P < .05). For further stage classification, the mean serum microRNA-122 level was higher in stage 1 (11.3±5.1, compensated cirrhosis) compared to stage 2~5 (8.5±4.2, 4.9±1.0, 4.7±1.6, 3.5±1.1, decompensated cirrhosis, all P < .05). The expression of serum microRNA-122 independent of Child-Pugh score and complications, including ascites, varices, HCC (P > .05).However it was affected by Meld score and Prothrombin time (P < .05). Moreover, ROC analysis indicated microRNA-122 could differentiate compensated HBV-related cirrhosis (0.97 of AUC, P < .01). Furthermore, it could differentiate patients in stage 1 (compensated cirrhosis without esophageal varices) from HBV-related cirrhosis (0.91 of AUC, P < .01), with a sensitivity of 77.8% and satisfactory specificity of 88.7%. The significance of the relationship between the decrease in serum microRNA-122 levels and the stage of liver cirrhosis will be beneficial. Conclusion: Our results strongly support the diagnostic value of serum microRNA-122 as a potential biomarker of stage classification in patients with HBV-related cirrhosis, which could facilitate risk stratification and careful management. Provide new biomarkers for the diagnosis of patients with hepatitis B cirrhosis.

Development and Validation of a Nomogram Predicting Postoperative Recurrent Lumbar Disc Herniation Based on Activity Factors.

Purpose: To develop an individualized predictive model for postoperative recurrent lumbar disc herniation (PRLDH) in patients undergoing percutaneous endoscopic transforaminal discectomy (PETD) by considering postoperative activity factors. Patients and Methods: Retrospectively collected data from 612 LDH patients who underwent PETD in our institution from January 2017 to June 2023. They were divided into a training group (429 cases) and a validation group (183 cases). Lasso regression (Model 1) and random forest (Model 2) were applied for variable selection in the training group. The two models were compared in terms of discrimination (the area under curve, AUC), calibration (calibration curve), and clinical utility (decision curve analysis, DCA). Akaike information criterion (AIC) was used for model comparison, and internal validation employed 1000 times Bootstrap + 10-fold cross-validation. Finally, a Nomogram was constructed to display the results and uploaded to the web version. Results: Among 612 treated LDH patients, 66 (10.78%) developed PRLDH. Model 1, superior in AUC, calibration, DCA, and AIC over Model 2, was chosen as the predictive model. Logistic regression in the training group identified BMI, smoking, activity level score, time to first ambulation, diabetes, Modic change, and Pfirrmann grade as independent predictors of PRLDH. Model 1 exhibited a training group AUC of 0.813 (95% CI 0.753-0.872) and a validation group AUC of 0.868 (95% CI 0.773-0.962). At a Youden index of 0.50, sensitivity was 0.73, specificity was 0.77. Internal validation (1000 times Bootstrap + 10-fold cross-validation) for the training group showed accuracy of 0.889, kappa consistency of 0.112, and AUC of 0.757. The Hosmer-Lemeshow goodness-of-fit tests indicated good discriminative ability for Model 1 in both the training (χ2=2.895, P=0.941) and validation groups (χ2=8.197, P=0.414). The DCA and Nomogram are accessible at https://sofarnomogram.shinyapps.io/PRLDHNom/. Conclusion: The Nomogram predictive model, developed based on postoperative activity factors in this study, demonstrates excellent predictive capability, facilitating risk assessment for the occurrence of PRLDH after PETD.

Effects of pre-formulation and post-cooking method on the rheological and gelation properties of 3D printed chicken products.

This study investigated the influence of oil type (olive, soybean, and peanut oil) and post-cooking methods (oven bake and microwave) on the quality of 3D printed chicken meat products. The Ostwald-de-Waele model was used to describe the flow behavior of chicken meat paste (R2 > 0.995). Oil-fortified groups present significantly lower consistency index (K) and flow behavior index (n), indicating better fluidity. A modified Cox-Merz rule was applied by multiplying angular frequency with shift factors (αSF). Surprisingly, the values of αSF are well-correlated with accuracy parameters of 3D printed cubes (|r| >0.8). For post-heating methods, baking results in higher fluid loss but contributes to a smoother surface. The microwaved gels showed better fluid retention ability and higher accuracy but lost the detail shape of the 3D printing model. Overall, the PO (peanut oil) meat emulsion group presented better textural properties and flat surfaces than other oil-added counterparts.

Feasibility study of Syngo iFlow in predicting hemodynamic improvement post-endovascular procedure in peripheral artery disease.

OBJECTIVE: This study endeavors to examine the feasibility of predicting the clinical outcomes of patients suffering from peripheral artery disease (PAD) who undergo endovascular intervention, by employing the Syngo iFlow technology. METHODS: Retrospectively enrolling 76 patients from December 2021 to May 2023, yielding a total of 77 affected limbs, this study employs clinical outcomes (improvement or otherwise) as the gold standard. Two physicians conducted visual assessments on both DSA and iFlow images to gauge patient improvement and assessed inter-observer consistency for each image modality. The Time to Peak (TTP) of regions of interest (ROI) at the femoral head, knee joint, and ankle joint was measured. Differences in pre- and post-procedure TTP were juxtaposed, and statistically significant parameter cutoff values were identified via ROC analysis. Employing these cutoffs for TTP classification, multivariate logistic regression and the C-statistic were utilized to assess the predictive value of distinct parameters for clinical success. RESULTS: Endovascular procedure exhibited technical and clinical success rates of 82.58 and 75.32%, respectively. Diagnostic performance of iFlow image visual assessment surpassed that of DSA images. Inter-observer agreement for iFlow and DSA image evaluations was equivalent (κ = 0.48 vs 0.50). Post-classification using cutoff values, multivariate logistic regression demonstrated the statistical significance of ankle joint TTP in post-procedure iFlow images of the endovascular procedure for clinical success evaluation (OR 7.21; 95% CI 1.68, 35.21; P = 0.010), with a C-statistic of 0.612. CONCLUSION: Syngo iFlow color-encoded imagery holds practical value in assessing the technical success of post-endovascular procedures, offering comprehensive lower limb arterial perfusion visualization. Its quantifiable parameters exhibit promising potential for prognosticating clinical success.

Safety and efficacy of a phage cocktail on murine wound infections caused by carbapenem-resistant Klebsiella pneumoniae.

OBJECTIVES: Carbapenem-resistant Klebsiella pneumoniae (CRKP) is a leading pathogen causing difficult-to-treat, healthcare-associated wound infections. Phages are an alternative approach against CRKP. This study established murine wound infection models with a CRKP clinical strain of sequence type 11 and capsular type KL64, which is the dominant type in China, carrying genes encoding KPC-2 and NDM-1 carbapenemases. METHODS: A cocktail was made comprising three lytic phages of different viral families against the strain. The phage cocktail restricted bacterial growth for 10 hours in vitro. The efficacy and safety of the phage cocktail in treating a murine wound CRKP infection were then evaluated. Mice were randomly assigned into four groups (16 for each) comprising a phage treatment group, infected with bacteria and 30 minutes later with phages, and three control groups administered with PBS (negative control), bacteria (infection control), or phages (phage control) on the wound. Wound tissues were processed for counting bacterial loads on days 1, 3, and 7 post-infection and examined for histopathological change on days 3 and 7. Two remaining mice in each group were monitored for wound healing until day 14. RESULTS: Compared with the infection control group, the wound bacterial load in the phage treatment group decreased by 4.95 × 102 CFU/g (> 100-fold; P < 0.05) at day 7 post-treatment, and wounds healed on day 10, as opposed to day 14 in the infection control group. No adverse events associated with phages were observed. CONCLUSION: The phage cocktail significantly reduced the wound bacterial load and promoted wound healing with good safety.

Diagnostic Value of Lower Extremity Venous Duplication via Digital Subtraction Angiography Guided Venography.

INTRODUCTION: Lower limb venous anomalies, including duplicated veins, are common and have significant impacts on the outcomes and efficacy of venous surgery. Digital subtraction angiography (DSA) guided venography, serving as the tertiary diagnostic option for venous disorders, offers valuable informations to clinical practitioners. PATIENTS AND METHODS: A retrospective study was conducted on 195 patients with suspected venous disease, evaluating 259 limbs with venography imaging. Two experienced interventional vascularists evaluated the images to determine the incidence and characteristics of variances in the femoral, popliteal, great saphenous, and small saphenous veins. Moreover, blood samples were collected to assess the safety of the venography procedure by monitoring changes in renal function. RESULT: Duplication variations were found in the lower limb veins, with the highest prevalence in the femoral vein (11.28%, 22/195), followed by the great saphenous vein (4.1%, 8/195), and the popliteal vein (1.54%, 3/195). No severe contrast agent allergies or postoperative complications were reported. No statistically significant differences were found in creatinine and urea levels pre- and post-operation for patients without duplication variations, those with duplication of the great saphenous, femoral, or popliteal vein (P < .05). CONCLUSION: DSA-guided venography is effective in identifying venous variations in lower limb disease. DFV is the most common recurrent vein, while DPV is the least. Adequate preparation ensures safety, high spatial resolution, dynamic imaging, and low tissue interference.

Study on remote sensing inversion and temporal-spatial variation of Hulun lake water quality based on machine learning.

Hulun Lake is facing significant water quality degradation, necessitating effective monitoring for safety. Traditional methods lack the necessary spatial and temporal coverage, underscoring the need for a remote sensing model. In this study, we utilized the Landsat 8 OLI dataset, incorporating cross-section monitoring and field sampling data comprehensively. Employing the random forest algorithm, we constructed a remote sensing inversion model for six water quality parameters in Hulun Lake: chlorophyll-a (Chl-a), total nitrogen (TN), total phosphorus (TP), ammonia nitrogen (NH3-N), chemical oxygen demand (COD), and dissolved oxygen (DO). The model was applied to the non-freezing period of Hulun Lake from 2016 to 2021, exhibiting commendable performance and generating high-resolution maps. Time series analysis revealed that during the study period, the pollution levels of TN, TP, and COD in Hulun Lake were extremely serious, exceeding the Class V water standard of China's surface water environmental quality standard. Regional analysis indicated lower pollutant concentrations in the central lake area compared to the lake inlet. The inflowing rivers with high pollution adversely impacted Hulun Lake's water quality. To ensure the continued health of Hulun Lake's water quality, it is imperative to monitor lake water quality attentively and implement necessary measures to prevent further deterioration. This study holds crucial importance for shaping and executing ecological protection and restoration strategies for Hulun Lake.

Targeting Diverse Wounds and Scars: Recent Innovative Bio-design of Microneedle Patch for Comprehensive Management.

Wounds and the subsequent formation of scars constitute a unified and complex phased process. Effective treatment is crucial; however, the diverse therapeutic approaches for different wounds and scars, as well as varying treatment needs at different stages, present significant challenges in selecting appropriate interventions. Microneedle patch (MNP), as a novel minimally invasive transdermal drug delivery system, has the potential for integrated and programmed treatment of various diseases and has shown promising applications in different types of wounds and scars. In this comprehensive review, the latest applications and biotechnological innovations of MNPs in these fields are thoroughly explored, summarizing their powerful abilities to accelerate healing, inhibit scar formation, and manage related symptoms. Moreover, potential applications in various scenarios are discussed. Additionally, the side effects, manufacturing processes, and material selection to explore the clinical translational potential are investigated. This groundwork can provide a theoretical basis and serve as a catalyst for future innovations in the pursuit of favorable therapeutic options for skin tissue regeneration.

3D PET/CT tumor segmentation based on nnU-Net with GCN refinement.

Objective. Whole-body positron emission tomography/computed tomography (PET/CT) scans are an important tool for diagnosing various malignancies (e.g. malignant melanoma, lymphoma, or lung cancer), and accurate segmentation of tumors is a key part of subsequent treatment. In recent years, convolutional neural network based segmentation methods have been extensively investigated. However, these methods often give inaccurate segmentation results, such as oversegmentation and undersegmentation. To address these issues, we propose a postprocessing method based on a graph convolutional network (GCN) to refine inaccurate segmentation results and improve the overall segmentation accuracy.Approach. First, nnU-Net is used as an initial segmentation framework, and the uncertainty in the segmentation results is analyzed. Certain and uncertain pixels are used to establish the nodes of a graph. Each node and its 6 neighbors form an edge, and 32 nodes are randomly selected as uncertain nodes to form edges. The highly uncertain nodes are used as the subsequent refinement targets. Second, the nnU-Net results of the certain nodes are used as labels to form a semisupervised graph network problem, and the uncertain part is optimized by training the GCN to improve the segmentation performance. This describes our proposed nnU-Net + GCN segmentation framework.Main results.We perform tumor segmentation experiments with the PET/CT dataset from the MICCIA2022 autoPET challenge. Among these data, 30 cases are randomly selected for testing, and the experimental results show that the false-positive rate is effectively reduced with nnU-Net + GCN refinement. In quantitative analysis, there is an improvement of 2.1% for the average Dice score, 6.4 for the 95% Hausdorff distance (HD95), and 1.7 for the average symmetric surface distance.Significance. The quantitative and qualitative evaluation results show that GCN postprocessing methods can effectively improve the tumor segmentation performance.

Study on spatio-temporal simulation and prediction of regional deep soil moisture using machine learning.

Deep soil moisture (SM) plays a crucial role in vegetation restoration, particularly in semi-arid areas. However, current SM products have limited access and do not meet the spatio-temporal scale and soil depth requirements in eco-hydrological research. Thus, this study constructs a random forest prediction model for SM at different depths by identifying driving factors and quantifying the correlation effect of vertical SM based on the international SM network dataset. Subsequently, the SMAP product is integrated into the model to expand SM from point scale to regional scale, yielding an SM data product with a suitable scale and continuous time and space. The results indicate that the correlation between precipitation and SM changes into the interaction between adjacent SM layers as the depth increases. The lag time of SM in the shallow surface layer (0-3 cm) to precipitation was 1 day, and there was no delay on the daily scale in the 3-20 cm layers of the three underlying surface types. The response time of 50 cm SM to 20 cm SM was 1-2 days in cropland and grassland and 2 days in forest. Slope, land use type, clay proportion, leaf area index, potential evapotranspiration, and land surface temperature were the key driving factors of SM in the Shandian River region. The random forest model established in this study demonstrated good prediction performance for SM at both site and regional scales. The obtained daily products had higher spatial fineness than CLDAS products and could describe the SM characteristics of different underlying surfaces. This study offers new ideas and technical support for acquiring deep SM data in arid and semi-arid areas of northern China.

The importance of temperature monitoring in predicting wound healing.

CONCLUSION: Upon wound formation, the wound temperature rises in the first 3-4 days until reaching its peak. It then falls at about one week after wound formation. In the second week after wound formation, the wound temperature decreases steadily to the baseline indicating a good wound condition and progression towards healing. While a continuous high temperature is often a sign of excessive inflammation or infection, which indicates urgent need of intervention and treatment.