Additionally, the BML models were further optimised with Random Search algorithms and compared to BML models with default hyperparameters. Comparing all 5 BML models, the GBR model shows the highest prediction accuracy with R2 of 0.96 and lowest model error with MAE and RMSE of 2.73 and 3.40, respectively for test dataset. In conclusion, the GBR model are the best performing BML for predicting the compressive strength of concrete with the highest prediction accuracy, and lowest modelling error.Predicting the compressive strength of concrete is a complicated process due to the heterogeneous mixture of concrete and high variable materials. Researchers have predicted the compressive strength of concrete for various mixes using machine learning and deep learning models. In this research, compressive strength of high-performance concrete with high volume ground granulated blast-furnace slag replacement is predicted using boosting machine learning (BML) algorithms, namely, Light Gradient Boosting Machine, CatBoost Regressor, Gradient Boosting Regressor (GBR), Adaboost Regressor, and Extreme Gradient Boosting. In these studies, the BML model’s performance is evaluated based on prediction accuracy and prediction error rates, i.e., R Concrete comprises four primary components: coarse aggregate, fine aggregate, cement, and water. Concrete's economic value allows it to be widely used in constructions and the accessibility to the material available in the local market. It also demonstrates excellent benefits over other construction materials such as steel, and concrete can be produced with minimum effort. In certain instances, supplementary materials like fly ash (PFA)3, blast furnace slag (GGBS)4, silica fume5, and other industrial waste/by-products are added in concrete to enhance the mechanical properties of the concrete4. The introduction of industrial waste/by-product7 into concrete offers environmental benefits while increasing the longevity and resiliency of concrete structures.Concrete has been commonly used in construction and architecture due to its favourable engineering properties. Concrete has the characteristics of rich raw material, low price, and high compressive strength and good durability8.Among the various concrete property indices, compressive strength is the most critical because it is directly related to the structural safety and is required for determining the performance of structures throughout their life, from new structural design to old structural assessment9. It is vital to have robust and reliable predictive models based on existing input and output data at the early stage to drive down the cost of making further experiments and reduce the cost associated with the risk of non-compliance concrete during construction5. With the use of suitable models, it can lead to success in finding combination inputs that can achieve meaningful outcomes and, at the same time, saves considerable time and money. However, empirical, and statistical models, such as linear and nonlinear regression, have been widely used. However, these models require laborious experimental work to develop, and can provide inaccurate results when the relationships between concrete properties and mixture composition and curing conditions are complex10.When dealing with concrete materials, one of the difficulties in selecting the appropriate materials and predicting the mechanical properties of the concrete, i.e., compressive strength, is due to cost and the availability of local material6. ML has been widely applied in the field of engineering to solve a variety of problems i.e., predict outages, estimate angular velocity, components failure prognostics and prediction of fatigue life14. In civil engineering, AI and ML have been previously employed to tackle problems in various structural engineering fields15. ML application is also used in building structural design & performance assessment, improving finite element modelling of structures, and enhancing concrete properties prediction & assessment20.ML is a sub-class of AI that self-learning through algorithms and improves its performance based on previous datasets/experience. The distinction between AI, ML, and DL is illustrated in Fig. 10. Table 10. Multiple Linear Regression (MLR)21, Support Vector Machine (SVR)23, Multilayer Perceptron (MLP)24, and Gradient Boosting26 are most used ML algorithms to predict the mechanical and chemical properties of concrete. In general, the compressive strength prediction was undertaken for several type of concrete i.e., ordinary concrete10, high-performance concrete30, ultra-high-performance concrete 20, and green concrete with supplementary cementitious material i.e., fly ash32, blast furnace slag4 and recycled aggregates6. ML/DL is also used to predict other mechanical and chemical properties of concrete, i.e., prediction of concrete shear strength24, 30], tensile strength33, flexural strength5, the thermal conductivity of concrete34, and chloride concentration of concrete35.Given the popularity of machine learning, especially in concrete technology, various studies have been conducted using ML/DL approaches38 was widely used in most previously reported studies. The use of boosting algorithms is not extensively reported in any previous studies except the GBR models. The proposed boosting algorithms were chosen based on their popularity and frequency in other research areas such as biomedical and construction hazard analysis, which reports that the BML models have higher prediction accuracy than other ML and DL models42. We implemented and analysed the accuracy and error of compressive strength prediction for five different boosting algorithms, namely LBGM, CATB, GBR, ADAB, and XGB. Additionally, the BML models are enhanced using the Random Search (RS) optimization process, which involves tuning the hyper-parameters of the BML algorithms.For the DL model, Artificial Neural Network (ANN)The study's objective is to identify the best performing BML models, i.e., LBGM, CATB, GBR, ADAB, and XGB to predict the HPC with high volume GGBS using BML algorithms, i.e., LBGM, CATB, GBR, ADAB, and XGB. The BML models were then optimised using the Random Search (RS) optimisation process by tuning the hyper-parameters of each BML model function. Additionally, comparison studies were also conducted using commonly used ML models, i.e., linear regression, decision tree, random forest, etc., to evaluate the performance of the BML model in predicting the concrete strength.The fundamentals behind BML algorithms models are defined in Sect. 2, followed by the statistical properties analysis of the dataset & modelling approach, findings from the optimised BML model, comparison studies between other ML models, and model validation results are provided in Sect. 3. The findings of each model’s prediction accuracy and modelling errors are concluded in Sect. 4.50. LBGM uses two innovative sampling techniques: Gradient-based One-Side Sampling (GOSS) and Exclusive Feature Bundling (EFB). GOSS excludes a substantial fraction of data instances with small gradients and uses the remainder to estimate the information gain. Since data instances with large gradients contribute more to the computation of information gain, GOSS can generate a highly accurate estimate of information gain with a significantly smaller data set.LGBM is a gradient boosting framework that uses tree-based learning algorithms developed by Microsoft50.EFB allows for the grouping of mutually exclusive features, hence reducing the number of features. It also demonstrates that while determining the optimal bundling of exclusive features, a greedy approach can reach an approximation ratio of relatively high. It was reported that LGBM speeds up the training process of conventional GBDT by up to over 20 times while achieving almost the same accuracy, and it is six times faster than XGBoostCATB is an open-sourced machine learning algorithm developed by Yandex in 2017. CATB is a decision tree algorithm based on gradient boosted decision trees. The algorithms in CATB models are a series of decision trees constructed sequentially, with each new tree having a lower loss than the prior trees. The starting parameters determine the number of trees generated, and overfitting is avoided using an overfitting detector. The processes of tree construction for a single tree in CATB algorithms include computing splits in advance, converting categorical features to numerical features, selecting the tree structure, and calculating values in leaves.52.Generally, CATB employed greedy algorithms in optimising the prediction accuracy. The features of CATB models are ordered according to their splits and are then substituted in each leaf. The depth of the tree and other constraints for structure selection is specified with pre-modeling parameters, and a random permutation of classification/regression objects is conducted before the construction of each new tree. CATB models validate the model performance with a metric that indicates the direction in which the function should be improved further when deciding the construction of the next tree. CATB model surpasses leading GBR packages and achieves new state-of-the-art performance on common benchmarks53.Friedman presented the GBR model as an ensemble method for regression and classification in 1999. The gradient boosting approach compares each iteration of the randomly chosen training set to the base model. In the GBR model, the lower the training data fraction, the faster the regression, as the model fits smaller data each iteration. GBR model requires the following tuning parameters: ntrees and shrinkage rate, where ntrees is the number of trees to be grown, and the shrinkage parameter, often referred to as the learning rate applied to each tree in the expansion54.This algorithm's fundamental foundation is 'boosting.' The boosting process aids in transitioning prediction from a 'weak' learner via the additive training process. The essential advantage of GBR algorithms is that it avoids overfitting and makes efficient use of computational resources by using an objective function. Besides improving output performance, GBR algorithms reduce the selected error function further29.ADAB, an acronym for Adaptive Boosting, is a meta-algorithm for statistical categorization developed in 2003 by Yoav Freund and Robert Schapire. It can be combined with a variety of other types of learning algorithms to enhance performance. The output of the other learning algorithms, i.e., 'weak learners,' is combined into a weighted sum representing the boosted classifier's final output. ADAB is adaptive because it adjusts succeeding weak learners favoring instances misclassified by previous classifiers/regressors. It is less prone to overfitting than other learning algorithms in some cases56.The individual learners in ADAB algorithms may be ineffective. Still, if their performance is marginally better than random guessing, the final model can be demonstrated to converge to a powerful learner. This technique benefits from a single best-fit decision model formed from the outcomes of several decision trees, each of which is constructed using a random selection of base features, i.e., decision factors from a training dataset45 to create state-of-the-art algorithms, the ‘extreme gradient boosting’23. The multiple Kaggle competition winner ‘XGBoost’ is a highly effective ML algorithm due to its scalable tree boosting system and sparsity-aware algorithm in modelling structured datasets. The algorithm has been the source of countless cutting-edge applications, and it has been the driving force behind many of these recent advances. It’s been widely used as industrial solutions such as customer churn prediction57, applicant risk assessment58, malware detection59, stock market selection60, classification of traffic accidents61, diseases identification40, and even in predicting the death of patience during SARS-COV-2(Covid-19) treatment42. The most significant benefit of XGBoost is its scalability across any condition62. In general, the XGBoost algorithms are the evolution of decision tree algorithms that were improved over time. Figure Extreme Gradient Boosting (XGB) or XGBoost is a decision tree-based ensemble ML algorithm that uses gradient boosting to make predictions for unstructured data. Tianqi Chen and Guestrin developed XGBoost, and the method uses the conventional tree gradient boosting algorithm63. Figure i.Data Collection – This entails collecting data from the laboratory and compiling it appropriately.ii.Data Pre-Processing – To correctly identify and arrange the acquired data, it is necessary to sort out the missing values and then normalise the dataset in preparation for model building.iii.Model Selection—For prediction and evaluation in this research, BML algorithms, i.e., LBGM, CATB, GBR, ADAB, and XGB, were utilised.iv.Hyper-parameter Optimisation – The RS approach was employed in each of the five proposed BML algorithms, and the results are compared to the original models.v.Model Validation—Validation and testing of the models were performed using the k-fold cross-validation approach, which randomly splits the dataset and minimises overfitting.vi.2, RMSE, MAE, MSE, RMSLE, MAPE.Model Evaluation – All the models are compared, and the best performing algorithms are selected based on evaluation metrics, i.e., Rvii.Analysis and Reporting – The findings in the case study are reported based on comparing various ML models, optimisation parameters, and evaluation metrics.For the most part, we utilised the Python programming language on Google's Colab platform to analyse the data and create the models. An open-source, low-code machine learning library ‘PyCaret’ was used in researchA total of 152 data of HPC compressive strength data were gathered from concrete trial mix conducted at a laboratory in Selangor, Malaysia. In general, the dataset is composed of seven concrete components: fine aggregate, coarse aggregate, ordinary Portland cement (OPC), ground granulated blast-furnace slag (GGBS), silica fume (SF), water, admixture, and moisture content (MC). The dataset also contains concrete compressive strength of a Grade 80 HPC, and the compressive strength results are available for 7, 28, 56, and 91 days. On average, each batch of concrete contains around 246 kg of GGBS and OPC, respectively.The proportion of cementitious content in each batch is around 45% of GGBS, 45% of OPC, and 10% of SF. Similarly, the ratio of fine to coarse aggregate is 1:1, equating to 70% of total concrete volume with a 0.25 water-to-cement ratio, or 138 kg of water in each batch of concrete. Additionally, the moisture content of fine and coarse aggregate was included as input parameters since the water content in each concrete batches was adjusted according to the moisture content in the aggregates. Details of statistical metrics are listed in Table The distribution correlations between the input parameters and the compressive strength are shown in Fig. 64. Pearson's correlation coefficient is a test statistic that shows the statistical link between two continuous variables. It is based on the covariance approach, in which the best method is considered for determining the relationship between two variables of interest. It reveals both the size of the association or correlation and the direction of the relationship. The correlation between all parameters was analysed for this research and visualized in Fig. Along with statistical and distribution analysis, a correlation coefficient study was performed to analyse the dataset and prepare for modelling. Pearson’s correlation coefficient approach indicated in Eq. As shown in Fig. 65, 65 Before training BML models, pre-processing data is required. To prevent training from being dominated by one or a few features with large magnitude, features should be normalised so that their range is consistent. The Z-score normalisation method was used in this study to normalise all values in a dataset so that the mean of all values is 0 and the standard deviation is 1. Equation The dataset's modelling proportion was randomly partitioned into two sets, i.e., training and testing dataset. Around 70% of the dataset was utilized for training the BML models, whereas 30% were used to test the modelsx: Original value.μ: Mean of data.σ: Standard deviation of dataset.Validation and testing of the models were performed using the k-fold cross-validation method illustrated in Fig. K-fold cross-validation enables the model to be trained and verified several times, resulting in a more accurate model with less overfitting. With the more traditional hold-out strategy, the dataset is partitioned into training, validation, and test sets, which reduces number of samples for model training. The model's performance is contingent upon a random selection of samples for the training, validation, and test sets.2), mean absolute error (MAE), root mean squared error (RMSE), mean squared error (MSE), root mean squared logarithmic error (RMSLE), and mean absolute percentage error (MAPE). These mathematical formulations are defined in Eqs. 2 would range from 0 to 1 – the closer the value is to 1, the higher fitting optimisation of the model is. The values MAE, RMSE, MSE, RMSLE, and MAPE are used to evaluate modelling error—the smaller the value, the lesser the difference between the predicted and measured values.In this paper, six separate statistical measurement parameters were used to calculate the prediction efficiency of the BML models. In simpler terms, the evaluation parameters estimate the accumulated error in predictions concerning actual observations. The statistical parameters are: coefficient of determination , are frequently used to explain and interpret ML modelsThe original dataset is updated for each feature by randomly shuffling the feature values. The model's evaluation metric for the updated dataset is computed and compared to the original dataset's evaluation metric. This procedure is repeated numerous times for each feature to get the mean and standard deviation of the permutation importance score.In this research, the permutation FIA was performed in all BML models to understand the influence of each feature/component of concrete in predicting the compressive strength of concrete. Figure 2 of 0.78. Similarly, both models produced prediction errors, i.e., MAE and RMSE of 4.17 and 5.0, respectively. Overall, the comparison models demonstrate that the initial BML model outperforms all other machine learning models.Subsequently, the initial BML models without optimisation was compared to 14 commonly used ML algorithms, including linear regression (LR), decision trees (DT), random forests (RF), and extra trees (ET), etc. Table Comparing all 5 BML models, the GBR model has outperformed the LBGM, CATB, ADAB, and XGB models. The GBR model optimised with RS algorithms achieved the highest prediction accuracy of 0.96 and the least prediction errors, with an MAE of 2.73, an RMSE of 3.40, and an RMSLE of 0.03. Notably, the RS algorithms optimisation technique improved the model prediction accuracy and reduced the modelling errors in all 5 BML models. Simultaneously, the evaluation of 14 commonly used ML models also suggests that the BML models have superior prediction accuracy and minimum prediction errors. These studies conclude that the optimised BML models, i.e., the GBR model are the best choice to predict the compressive strength of concrete, mainly for HPC and concrete with high volume GGBS replacements. For future research, a comparison study between ANN models with BML models or hyperparameter tuning with different optimisation algorithms, i.e., Grid Search, can be evaluated and compared with the proposed BML model's performance.Supplementary Information.


Congenital pseudarthrosis of the tibia (CPT) is a rare and difficult-to-treat congenital disease in neonates. Our previous study found that exosomes derived from serum of children with CPT inhibit bone formation. In this study, we used ultrasound bone densitometry to detect the bone strength differences between hospitalized children with CPT and with non-metabolic diseases to determine the bone strength of children with CPT.A total of 37 children with CPT with a mean age of 3.14 ± 1.81 years and 40 hospitalized children with a mean age of 3.32 ± 2.66 years with supracondylar fracture of the humerus and without a bone metabolic disease (control group) were recruited in our hospital. The ultrasonic bone densitometer was used to examine the bilateral calcaneus of the subjects. We collected the broadband ultrasonic attenuation (BUA), speed of sound (SOS), quantitative ultrasound index (QUI), bone strength index (STI) and bone mineral density estimation (BMDe) values. Multivariable regression was used to examine the associations between quantitative ultrasound measurement differences and age, body mass index (BMI), neurofibromatosis type 1 (NF1) and CPT Crawford type. Intra-class correlation coefficient (ICC) was calculated to estimate intra- and inter-rater agreements.3) than the control . Multiple regression revealed that SOS, STI and QUI were statistically significant and negatively correlated with CPT Crawford classification.74 calcaneus scans were taken from CPT patients (23 boys and 14 girls) and 80 calcaneus scans were taken from the control (24 boys and 16 girls). The CPT patients exhibited significantly lower SOS , STI (7.2319 ± 38.6525), QUI (8.2532 ± 56.1720), and BMDe (−0.0241 ± 0.3552 g/cmWe found the incidence of decreased bone strength in CPT group was higher than that in the non-bone metabolic disease group. This phenomenon was not related to NF1 but related to CPT Crawford classification, which suggested that the higher the grade of the CPT Crawford classification, the lower the bone strength and the higher the risk of fracture. Congenital pseudarthrosis of the tibia (CPT) is a rare and difficult-to-treat congenital disorder in newborns with an incidence of 1/140,000–1/250,000 , 4. In oStudies have shown that children with CPT are usually associated with neurofibromatosis type 1 (NF1), a disorder in which there is a loss of function of the NF1 gene, and CPT is also a rare manifestation of NF1 , 9. DuriBone strength reflects the ability of a bone's resistance to fracture for a given condition, and bone stiffness index (STI) and bone mineral density estimation (BMDe) are important parameters for evaluating bone strength . QuantitAs children with CPT are always associated with NF1 symptoms, and tibial pseudarthrosis is clinically difficult to cure, we hypothesized that these conditions may be caused by abnormalities in systemic skeletal metabolism. In this study, we used ultrasound bone densitometry to measure bone strength in children with CPT vs. hospitalized children suffering supracondylar fracture of the humerus without a metabolic bone disease to detect the bone strength in children with CPT.A cross-sectional study design was used to compare bone strength in CPT children with NF1 and hospitalized children without a bone metabolic disease. Informed consent was granted from all participants' parents. All data were analyzed after obtaining approval from the Ethics Committee of Hunan Children's Hospital.Thirty-seven children with a mean age of 3.14 ± 1.81 years with a diagnosis of CPT who had not received any previous treatment and 40 hospitalized children with a mean age of 3.32 ± 2.66 years suffering with supracondylar fracture of the humerus without a metabolic bone disease were included in this study. Participants were excluded if they had any known bone disease, other chronic diseases, previous or current treatment that might affect bone metabolism , or if the child was unable to co-operate with the study protocol.All data were collected by the same researcher (S.X.), ensuring that all measurements were taken in the same way. General information was collected, including name, age, sex, and body mass index (BMI). The ultrasonic bone densitometer  was used to examine the bilateral calcaneus of the subjects. The probe was placed correctly and faced the heel to avoid errors in the measurement results. The measured data were automatically analyzed by the computer system. According to the measurement method, we could obtain the BUA and SOS values, and then refer to the methods of calculating the QUI, STI and BMDe values , 19. To Broadband ultrasound attenuation (BUA) , 19: UltSpeed of sound (SOS) , 19: TheBone strength index (STI) , 19: AccQuantitative ultrasound index (QUI) , 19: StaBone mineral density estimation (BMDe) formula , 19: Magt-tests were used to determine within-group differences for various quantitative measures of quantitative ultrasound. For between-group analysis, t-tests were used to determine differences in various quantitative measures. Multivariate liner regression was used to investigate the relationship between differences in quantitative ultrasound measurements and age, BMI, NF1, and CPT Crawford type. P < 0.05 was considered statistically significant.All data were expressed as mean ± standard deviation and processed by STATA . The intraclass correlation coefficient (ICC) was calculated to estimate intra- and inter-rater agreement. According to Landis' definition, an ICC of 0.6–0.8 was considered good agreement and >0.8 was considered excellent agreement. Paired In total, we reported 37 pairs of calcaneus scans from CPT patients and 40 pairs of scans from the controls. Among the CPT patients, 19 were Crawford type-II, and 18 were Crawford type-IV. The demographic characteristics of the CPT patients and controls are shown in The quantitative ultrasound measurements between CPT patients and controls are presented in For the above statistically significant parameters, we selected SOS, STI, QUI and BMDe as dependent variables and defined age, BMI, gender and NF-1 as independent variables. The final multiple linear regression model was not statistically significant and the regression coefficients of the measurements obtained by quantitative ultrasound with age, gender, BMI and NF-1 were not statistically significant .We further analyzed the effects of age, sex, BMI, and Crawford classification of pseudarthrosis on SOS, STI, QUI, and BMDe. The final regression model showed that STI was positively correlated with age, while SOS, STI, and QUI were all negatively correlated with gender and CPT Crawford classification .CPT is a rare disease in pediatric orthopedics. Once a fracture of the tibia occurs, it rarely heals naturally and usually results in a persistent pseudarthrosis. The treatment of CPT remains a surgical challenge, and fracture healing is difficult regardless of the surgical approach chosen . There aRecently, quantitative ultrasound has been introduced as a detection tool for orthopedic diseases, and its application in pediatric patients is also expanding . PreviouIn this study, quantitative ultrasound was used to detect the bone mineral density parameters of children with CPT and those with non-bone metabolic diseases. The incidence of osteopenia in the CPT group was higher than that in the control group, and the SOS, STI, QUI, and BMDe of CPT children were lower than those of children with non-bone metabolic diseases. SOS is an index for evaluating bone strength, which is proportional to bone mass and can better predict the risk of fracture . TherefoStudies have found that NF1 affects systemic bone metabolism , 25, andThis study has some limitations. The above results obtained by cross-sectional studies require long-term follow-up, and the sample size may be small. In addition, children with CPT suffer from immobilization and pain of the affected limb which may lead to a reduction in their physical activity, and the change of bone mineral density may also be related to this. There is also a lack of activity scales to quantitatively assess children with CPT, thus, in future studies, we should recruit more subjects and identify more parameters to reduce the effects of the above impact factors. The design of an activity scale for children with CPT is also a topic for our future research.In conclusion, by recruiting children with CPT and those with non-bone metabolic diseases, we found that the incidence of osteopenia in the CPT group was higher than that in the non-bone metabolic disease group, and SOS, STI, QUI and BMDe in the CPT group were lower than in the non-bone metabolic disease group, and this phenomenon is not related to NF1 but is related to CPT Crawford classification, suggesting that a higher CPT Crawford classification is associated with lower bone strength and higher risk of fracture.The original contributions presented in the study are included in the article/supplementary material, further inquiries can be directed to the corresponding author/s.The studies involving human participants were reviewed and approved by the Institutional Review Board of Ethics Committee of Hunan Children's Hospital (protocol code HCHLL-2021-129). Written informed consent to participate in this study was provided by the participants' legal guardian/next of kin. Written informed consent was obtained from the individual(s), and minor(s)' legal guardian/next of kin, for the publication of any potentially identifiable images or data included in this article.GY and HM: conceptualization. HY: methodology. SX, GZ, and YL: validation. GY: formal analysis, investigation, data curation, and writing—original draft preparation. HM: resources, project administration, and funding acquisition. GY, HY, and HM: writing—review and editing. HM and HY: supervision. All authors have read and agreed to the published version of the manuscript.This research was funded by National Natural Science Foundation of China (Grant No. 82101818) and Key Research and Development Program of Hunan Province (2020SK2113).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.


Elderly patients with multiple organ dysfunction syndrome (MODS) have a higher mortality during hospitalization in the intensive care unit (ICU). Elderly patients often suffer from malnutrition. On the basis of the MIMIC-III database, this study analyzed the effect of the baseline nutritional status on the death of elderly patients with MODS during hospitalization.Elderly patients with MODS were screened out from MIMIC-III 1.4 database. The geriatric nutritional risk index (GNRI) was calculated and used to group patients into: normal nutrition (GNRI > 98) and malnutrition (GNRI ≤ 98) groups. The malnutrition group was divided into mild (92–98), moderate (82–91), and severe (≤81) groups. The differences in the baseline data and the incidence of adverse events between groups were compared. The GAM model was used to determine whether a curve relationship was present between the hospital death of elderly patients with MODS and GNRI and analyze the threshold saturation effect. The multivariate logistic regression was used to calculate the odds ratio (OR) of in-hospital deaths in different GNRI groups. The interaction test was performed to find subgroups with differences.P < 0.001; OR = 0.59, 95% CI: 0.48–0.72). The GAM model fitting analysis showed a threshold saturation effect at GNRI = 92. Adjusted OR values with GNRI ≥ 92 began to change to 1, and GNRI and death had no association. At GNRI < 92, high GNRI related to low risk of death. Subgroup analysis of patients with GNRI < 92 showed that the risk of death in elderly male patients was lower than that of female patients.A total of 2456 elderly patients with MODS were enrolled. A total of 1,273 (51.8%) and 1183 (48.2%) patients were in the normal nutrition and malnutrition groups, respectively. The mortality rate of patients in the normal nutrition group during hospitalization was lower than that in the malnutrition group (206/1273 vs. 292/1183, X2 = 27.410, GNRI is related to the severity of illness in elderly patients with MODS. At GNRI < 92, moderate to severe malnutrition increases the risk of death in elderly patients with MODS during hospitalization. With the extension of human life span, the number of elderly patients is increasing, and the number of elderly patients admitted to the intensive care unit (ICU) also increases . The morMalnutrition has an adverse effect on the long-term prognosis of patients and has a high incidence in the elderly due to various comorbidities, strict dietary control and decreased appetite. Malnutrition is common in patients with chronic heart failure, renal failure, respiratory failure, and long-term consumption of malignant tumors . HoweverThe MIMIC database provides a large number of real-world clinical data of critically ill patients. In recent years, this database has been deeply excavated and has produced many results with clinical application value . The pur2 are measured at least once. The exclusion criteria are as follows: (1) loss of key data, such as the first SOFA and the first simplified acute physiology score I and (2) loss to follow-up. All patient-related information in the MIMIC-III database is anonymous, and no informed consent is required.The subjects of this study are elderly patients with MODS admitted to the ICU recorded in the MIMIC-III database. The inclusion criteria are as follows: (1) age ≥ 65 years; (2) first admission to ICU ; (3) retention time in ICU ≥ 24 h; (4) sequential organ failure (SOFA) score ≥ 2 points and involvement of at least two organs; and (5) HR, RR, MAP, GCS, T, and SPOThe data of this study come from the MIMIC-III database, an open critical medicine database jointly released by the Massachusetts Institute of Technology Computational Physiology Laboratory, Beth Israel Dikon Medical Center, and Philips Medical under the funding of the National Institutes of Health. The latest version is the MIMIC-III v1.4. This database collects the hospitalization information of more than 50,000 patients admitted to the ICU of Beth Israel Dikang Medical Center in the United States from 2002 to 2012. Data include vital signs, medications, laboratory measurements, observations, records drawn by nursing staff, fluid balance, surgical codes, diagnostic codes, imaging reports, hospital stay, and survival data. This database has passed ethical review and obtained right for use.+, Na+, and Ca2+), blood HCO3−, SOFA score, ICU hospital stay, death in the ICU, and other data. Complications ; use of mechanical ventilation, continuous renal replacement therapy during ICU hospitalization. All laboratory test parameters are extracted from the data generated within the first 24 h after the patient enters the ICU  and extreme values during the ICU hospitalization period .The PostgreSQL 10.7 software and SQL language are used to extract the following data from the MIMIC-III database: age, gender, weight, white blood cell count, hemoglobin, platelet count, blood urea nitrogen, blood creatinine, blood glucose, blood electrolytes ]. GNRI > 98 indicates normal nutritional status, and GNRI ≤ 98 means malnutrition .Groups are based on the GNRI. GNRI is calculated on the basis of height (m), weight (kg), and ALB level (g/L). The formula is: GNRI = 1.489 × ALB + 41.7 × . The Wilcoxon rank–sum test is used to compare the two groups, and the Kruskal–Wallis test is used for comparison between groups. Categorical variables are expressed as percentages (%), and comparisons between groups are performed using the χAfter screening, 2,456 elderly critically ill patients were included . PatientAmong all patients, 1,875 had acute kidney injury, and all patients had sepsis. A total of 2042 (83.1%) patients had a GCS score of 15, a shock index of 0.26–2.94 with a median of 0.72 , and SOFA score of 2–21 with a median of 5 . A total of 1496 patients received mechanical ventilation, and 127 patients received CRRT. The comparison between each group is shown in Among all patients, 498 died during hospitalization. The median length of hospitalization was 10  days, and the median length of ICU hospitalization was 4  days. The mortality, length of stay in hospital, and ICU stay in the normal nutrition group were lower than those in the malnutrition group . SubgrouA total of 206 (16.2%) and 292 (24.7%) patients died during hospitalization in the normal nutrition and malnutrition groups, respectively. Malnutrition significantly increased the mortality risk of elderly patients with MODS during hospitalization . After adjusting for confounding factors, a curve fitting equation was made for death during hospitalization and GNRI by using the GAM model. A non-linear relationship between death during hospitalization and GNRI was observed, and the slope changed significantly, which might have a threshold saturation effect . The thrP < 0.001; P for interaction > 0.05). In the results of gender stratification, the risk of death for older men was lower than that for older women  further increased the mortality of elderly severely ill patients during hospitalization . Further univariate analysis showed that moderate to severe malnutrition further increases the risk of death in elderly patients with MODS during hospitalization . For patients with MODS with GNRI < 92, GNRI is the protective factor, that is, a high GNRI results in low risk of death. Further subgroup analysis of 739 elderly patients with GNRI < 92 shows that the risk of death in elderly men is lower than that in elderly women. The results of this study suggest that mild malnutrition has no significant effect on the mortality risk of elderly patients with MODS during hospitalization, but elderly patients with MODS and moderate to severe malnutrition have high risk of death during hospitalization, and it is reasonable for patients to be evaluated upon admission to the ICU. The nutritional status of the baseline level is helpful in judging the treatment effect during hospitalization and suggests the necessity of nutritional support for elderly patients with MODS. The goal of nutritional support may be GNRI > 99, but accurate conclusions need further confirmation by prospective interventional studies.This study found through multiple analyses that GNRI, which reflects the nutritional status of elderly patients, is closely related to the outcome of elderly patients with MODS during hospitalization. The univariate analysis showed that malnutrition (GNRI ≤ 98) significantly increases the risk of death during hospitalization in elderly patients with MODS  increases significantly, leading to a continuous increase in the number of elderly patients admitted to ICUs . ElderlyNutrition plays an important role in the normal physiological functions of the human body and treatment of diseases especially in elderly patients , 20. CurThis study has certain limitations. The main reason is that the data of this study come from the MIMIC database. Even with its large inventory sample size, this study remains a retrospective analysis. As a result, some cases may be eliminated due to incomplete data. At the same time, some useful indicators are not tested or entered, which may affect the results of the analysis. Another limitation is that multivariate logistic regression equation was used to calculate the odds ratio (OR) of in-hospital deaths among different groups, but the real-world data may not be linear. For a reliable evidence, further multicenter registration studies, especially prospective cohort studies, are still needed.GNRI is related to the severity of illness in elderly patients with MODS. When GNRI < 92, moderate to severe malnutrition increases the risk of death in elderly patients with MODS during hospitalization. In clinical practice, whether elderly patients with MODS have malnutrition should be determined. For patients with malnutrition, reasonable supplementary nutrition should be given to avoid poor prognosis due to malnutrition.The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.Ethical review and approval was not required for the study on human participants in accordance with the local legislation and institutional requirements. Written informed consent for participation was not required for this study in accordance with the national legislation and the institutional requirements. Written informed consent was not obtained from the individual(s) for the publication of any potentially identifiable images or data included in this article.FZ contributed to the study initial design. ZM and TW performed the statistical analysis. XL, JC, PH, CL, HL, HK, and ZZ contributed to the data collection and data cleansing. ZM made the charts and drafted the manuscript. All authors read and approved the final manuscript.This study was supported by Medical Innovation Research (18CXZ026) and Medical Comprehensive Program (20BJZ27). The funding sources had no role in study design, data collection, data analysis, data interpretation, or writing of the report.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.


Blattella germanica. Besides their role in killing pathogenic bacteria, AMPs could be involved in controlling its symbiotic systems (endosymbiont and microbiota). We found that the IMD pathway was active in the adult female transcriptomes of six tissues  and hemolymph. Total expression of AMP genes was high in hemolymph and salivary glands and much lower in the other sample types. The expression of specific AMP genes was very heterogeneous among sample types. Two genes, defensin_g10 and drosomycin_g5, displayed relevant expression in the seven sample types, although higher in hemolymph. Other genes only displayed high expression in one tissue. Almost no expression of attacin-like and blattellicin genes was observed in any sample type, although some of them were among the genes with the highest expression in adult female whole bodies. The expression of AMP genes in salivary glands could help control pathogens ingested with food and even determine gut microbiota composition. The low expression levels in midgut and hindgut are probably related to the presence of beneficial microbiota. Furthermore, a reduction in the expression of AMP genes in fat body could be the way to prevent damage to the population of the endosymbiont Blattabacterium cuenoti within bacteriocytes.Antimicrobial peptide (AMP) genes, triggered by Toll and IMD pathways, are essential components of the innate immune system in the German cockroach  Blattella germanica (Linnaeus) is a pest that affects human environments around the world. It impacts human health in several ways, including the transmission of pathogens or by disseminating antibiotic-resistant bacteria. How B. germanica, like other cockroaches, has evolved to become a human pest, adapted to unhealthy habitats, is of great interest. Genomics resources are providing molecular understanding of adaptation and immune response. The genomes of some species of cockroaches such as Periplaneta americana (Linnaeus) [B. germanica [Most species of cockroaches (Blattodea) live in tropical/subtropical regions, and only a few interact with humans and may be considered pests . The Gerinnaeus)  or B. geermanica , in combermanica , have maBlattabacterium cuenoti, hereinafter Blattabacterium) located in bacteriocytes  in the fat body and ectosymbionts (a rich and varied microbiota) located in the hindgut [Blattabacterium genomes revealed that the endosymbiont is involved in the nitrogen metabolism of the host, supplying urease, which is responsible for producing ammonia in the final step of the degradation of uric acid (the nitrogen storage compound of cockroaches). Ammonia can be incorporated into glutamate and glutamine by the endosymbiont and the host, respectively, participating in the production of essential amino acids for the host [However, cockroaches also interact with other non-pathogenic or beneficial bacteria. In fact, cockroaches are paradigmatic, as two symbiotic systems coexist in each individual: a bacterial endosymbiont , which provide a better defense against pathogens [B. germanica, that encode proteins with an N-terminal signal peptide, a long middle Glx-rich region and an attacin-C domain at the C-terminus.Pathogens induce the activation of one or two signaling pathways, namely the immune deficiency (IMD) pathway, which is preferentially activated by Gram-negative bacteria, and the Toll pathway, which is preferentially activated by Gram-positive bacteria and fungi, triggering the expression of multiple AMP genes ,17. In Bathogens . BlattelDrosophila that AMPs, and lysozymes to a lesser degree, determine the bacterial community composition and abundance of the microbiota in the gut [B. germanica has a rich and varied microbiota, this would imply not having a strong immune response in the midgut or hindgut, or that most species of the microbiota were selected to resist the effect of AMPs more efficiently than pathogens. In addition, it has also been found that AMPs participate in the maintenance and control of endosymbiosis in plants and animals. This was demonstrated in the insect Sitophilus with the endosymbiont Sodalis pierantonius [Rhizobium [Alnus with Frankia [Alnus, AMPs are involved in the permeabilization of the bacterial membranes, presumably allowing the metabolic complementation with the host.Furthermore, it has been proposed that AMPs not only have a defensive role against pathogens but also play a part in regulating the interaction of the eukaryotic host with its mutualistic symbionts ,19. In t the gut . Given tantonius ,22,23, ahizobium  and of A Frankia . In leguB. germanica adult females, with the aim of understanding the way in which the expression of AMPs kills pathogens, maintaining a healthy gut microbiota and regulating the bacterial endosymbiont located in the fat body. We also sought to identify the genes involved in the IMD pathway and analyze their expression, because IMD is probably the main signaling pathway required for the production of those AMPs and may be required for the control of the endosymbiont and for the homeostasis of gut microbiota.In this study, we report the levels of expression of AMP genes in six types of tissue and hemolymph of B. germanica  were identical to the annotated CDS of the genome; in other cases, there were differences of at least one segment, due to the prediction of a different gene structure. The locus tag qualifiers of CDS with complete or partial coverage are indicated  and hemolymph by estimating the means of the normalized expression (GeTMM) .rel gene, encoding Relish, a key downstream transcription factor involved in the expression of AMP genes [dsp1, eff and SkpA, are highly transcribed in all of the analyzed samples over 102 GeTMM.Most of the genes were expressed in the seven sample types. For example, the MP genes , is trancad, CASP, Duox, Npc2, RYBP and Skp2). For example, the cad gene , which in Drosophila functions as a gut-specific transcriptional repressor of NF-κB–dependent induction of AMP genes [CASP gene was only substantially expressed in midgut. It encodes Caspase-3, a member of the caspase family of cysteine proteases, previously described as inducing apoptosis in the midgut of P. americana under starvation conditions [Npc2 (Niemann-Pick type C-2), but its expression took place mainly in midgut. The most probable reason for such a high expression is its role in the availability of sterol substrate, as is the case for some Drosophila Npc2 genes [Npc2d was one of the differentially metabolic overexpressed genes detected in Drosophila when comparing normal (with microbiota) to germ-free adult midguts [Furthermore, some genes were differentially expressed in one or more sample types  in only one sample . However, it was relevant that genes that are relatively highly expressed in whole bodies, such as blattellicin_g4 and attacin-like genes  or in salivary glands . Some genes displayed very high expression (>103 GeTMM), others high expression (>102 GeTMM), and others moderate expression (>101 GeTMM). The expression of the other two types of AMP genes, attacin-like and blattellicin genes, is shown in Because hemolymph and salivary glands were the sample types with the highest total AMP gene expression, we analyzed defensin and drosomycin genes . Most ofBlattabacterium, and in some insects the fat body is an important organ involved in the production of AMPs for the hemolymph [attacin-like_g2 and attacin-like_g3 was due to one out of the four replicas. In this, the GeTMM value was higher than 102, while in the three others, the value was smaller than 101. Although low, fat body was the sample type with the highest expression level of some genes such as drosomycin_g9, termicin_g2 and termicin_g3 . The expression of the different AMP genes is triggered as a consequence of the detection of the invasive microorganisms (infecting microbes) by two major NF-kB-mediated signaling pathways: IMD (which provides protection mainly against Gram-negative bacteria and some Gram-positive bacteria) and Toll (which provides protection mainly against fungi and other Gram-positive bacteria) . Two maiB. germanica lives in a hostile environment in the presence of  pathogenic bacteria and in consequence displays a large arsenal of AMPs. The AMP gene repertoire of B. germanica (39 genes) has derived from the expansion of the five types of AMP gene families [Nasonia vitripennis  [Musca domestica (Linnaeus) [P. americana [B. germanica of the most expanded defensin and drosomycin gene families [families ,35. Comp  or the 3innaeus)  (summariinnaeus) ), and mumericana . The phyfamilies  revealedB. germanica transcriptomic projects, with the exception of the IKKbeta, IKKg and key genes .The expression of all the genes involved in the IMD signaling pathway has been detected in adult ey genes . While Idefensin_g9, defensin_g10, and drosomycin_g5, and those in salivary glands were defensin_g3-g5 and defensin_g15-16.We observed that the highest levels of total AMP gene expression, among the analyzed tissues, were detected in salivary glands and hemolymph. Most genes display tissue specificity. Those with the highest expression in hemolymph were B. germanica hemolymph, it must be taken into consideration that the samples come from individuals grown under controlled conditions, and that in a challenge situation with diverse pathogenic bacteria, both the levels and the diversity of AMPs produced could be increased.Although we did not detect the expression of all AMP genes in B. germanica, this response is not observed in the different parts of the gut , where total AMP gene expression is very low. Moreover, some AMPs (symbiotic AMPs) are also produced by eukaryotic hosts during their symbiotic interaction with bacteria, counterintuitively not to kill but to control the symbiotic bacterial population [The large amounts of several AMPs produced by the salivary glands imply that the control of ingested pathogens in the digestive system starts after mixing the saliva with the ingested food. This expression of AMP genes agrees with the idea that anterior parts of the digestive system encounter ingested bacteria first and might need to invoke a stronger response than distal parts . In factpulation ,19. Furtpulation .Hydra, the composition of the microbiota is determined by AMPs produced by the epithelial cells in contact with the microbiota [Drosophila, where if the expression of some AMP genes is canceled, a change in the microbiota is triggered [Drosophila, where some production of AMPs takes place in the midgut [B. germanica, the majority of AMP production in the digestive system is detected in the salivary glands. Similarly, high expression of an AMP gene has also been observed in the salivary glands and midgut of Bemisia tabaci (Gennadius) [Ornithodoros turicata (Dugès) [In crobiota . In someriggered ,42. As ce midgut , our resnnadius) , and som (Dugès) . In inse (Dugès) , althougB. germanica fat bodies may increase if different types of microbes reach their cells, since in insects it is an immune-responsive tissue [Blattabacterium in bacteriocytes.In most insects, the fat body is an organ that can produce large amounts of AMPs during infection that are released to hemolymph ,46. Altee tissue . HoweverRhizobium bacteria, several hundred AMPs (nodule-specific cysteine-rich peptides) allow the plant to manipulate the physiology of the bacterial symbiont [Sitophilus [A. pisum, some cysteine-rich AMP-like polypeptides are specifically expressed in bacteriocytes, cells containing the bacterial endosymbiont Buchnera aphidicola [B. germanica, the massive production of AMPs that could carry out this function has not been detected, although the existence of unidentified AMP-like genes, previously undetected [It has been proposed that AMPs are also involved in endosymbiotic associations, controlling the bacterial population and allowing metabolic complementation between the eukaryotic host and the endosymbiont. Symbiotic AMPs can affect endosymbionts through various mechanisms, including interaction with the bacterial membrane  or targeting intracellular machinery and interfering with bacterial metabolism . In the symbiont . In insetophilus , while ihidicola , and somhidicola . In B. gdetected , cannot attacin-like_g2 and attacin-like_g3 in one out of the four samples of fat body, perhaps due to a contamination of surrounding tissues. The most probable place for their expression in adult bodies is the abdomen close to the heart, where the periostial hemocytes are attached and induce, after infection, the aggregation of additional hemocytes. This integrated immune and circulatory system was recently described as a general trend in insects [B. germanica, in which it was detected that hemocytes were located in the dorsal tergum and almost absent in the ventral sternum [attacin-like_g1, attacin_like_g2 and blattellicin_g1 genes in B. germanica gut is significantly increased after feeding with live Salmonella enterica serovar Typhimurium [defensin_g1-g2 was also detected at very low levels in control individuals by qRT-PCR (approximate range 10−4 to 10−5) [EF1A), except for attacin-like_g1, which was not detected at all in our samples .Finally, in adult whole bodies, attacin-like and blattellicin genes are among the most highly expressed . However insects . One of  sternum . Howeverhimurium . In thisto 10−5) . The levB. germanica is mainly located in hemolymph and salivary glands. We have also shown that although some genes are expressed in most tissues, others are tissue-specific. This differential expression in the digestive system and fat body may be related to avoiding negative effects on the beneficial microbiota and the endosymbiont, while maintaining the removal of pathogens.In summary, as we have described, the expression of AMP genes in adult B. germanica, we performed a search for homologous sequences, using as starting data the Innate Immunity Genes in Insects (4IN) database of the University of Lyon, which is a comprehensive database of innate immunity genes in a diverse range of available insect genomes. The multifasta files obtained after the 4IN search were subjected to multiple alignment with MAFFT v7.475 [B. germanica gene databases. Sequence searches were performed on the B. germanica genome CDS set, which was obtained from GCA_003018175.1  to recursively perform the processing for each gene and for each database used. The final results were confirmed with blastx searches and modified when required.In order to identify the genes that constitute the IMD immune signaling pathway in T v7.475  using thT v7.475  programsB. germanica contains many assembly gaps. Data extraction from SRA projects was performed with fasterq-dump (NCBI SRA Toolkit v2.11.0 package). The quality of reads was checked with FastQt v0.2.3 . Correction of poor quality reads was performed with Rcorrector v1.0.4 [Transcriptomes used as databases in which to search for homologous sequences were assembled from Sequence Read Archive (SRA) projects. The assembling was performed de novo rather than with mapping due to the fact that the genome of r v1.0.4 . Trimmomr v1.0.4  was usedr v1.0.4  was usedB. germanica, it was not able to identify the proteins unequivocally. To avoid false positives and hits with incomplete sequences, the results were thoroughly checked. The CDS harbored by the individual transcripts were obtained with getorf, from the EMBOSS v6.5.7 package [While HMMER was able to detect which sequences had a higher degree of homology in  package , with a  package  and Spid package . The res package  was usedB. germanica originating from a laboratory population housed by Dr. X. Bellés’s group at the Institute of Evolutionary Biology  was raised in plastic containers at a temperature of 25 °C and a relative humidity of 60%, in 12/12 h light/dark cycles in climatic chambers at the Institute for Integrative Systems Biology . The diet was based on dog food  and water provided ad libitum. Adult individuals were collected from different containers to avoid population bias, between 0 and 48 h after the transition from nymph to adult, which is considered day 0. Only females were selected to avoid bias due to sexual dimorphism, and all the sampling was carried out at day 5 of adult life.A population of 2 sedation and cleaned with 10% bleach, 70% ethanol and double washed with Type II water. They were fixed with entomological needles in supine position on a silicone plate, and the following tissues were extracted: salivary glands , foregut , midgut , hindgut , Malpighian tubules , and fat body . Samples were collected in previously cooled Eppendorf tubes, treated overnight with RNAlater, frozen the next morning with liquid nitrogen and stored at −80 °C until RNA extraction.The cockroaches were subjected to CO2 and fixed with entomological needles in supine position on a silicone plate. Subsequently, one of the legs of the third pair was cut at the beginning of the second segment. Hemolymph was collected by capillarity by massaging the abdominal area. Hemolymph was collected directly in TRI Reagent (hemolymph to reagent ratio 1:3), and samples were frozen in liquid nitrogen and stored at −80 °C until RNA extraction.For the collection of hemolymph samples , individuals were sedated with COServei Central de Suport a la Investigació Experimental . RNA integrity and quality, as well as mRNA enrichment, were analyzed before proceeding with library preparation. Sequencing was performed with an Illumina NextSeq 550, resulting in single-end reads of 150 nucleotides each.RNA was extracted from the tissues with the NucleoSpin RNA kit (Macherey-Nagel), while hemolymph RNA was extracted with Direct-zol RNA miniprep kit (Zymo Research), both according to the manufacturer’s recommended instructions. Samples were quantified with Nanodrop and Qubit. Sequencing was carried out at the B. germanica AMPs to the database.To make a side-by-side comparison of the expression levels of the different AMP genes  in each of the tissues, the reads were quantified and normalized. Residual adapters were cleaned with Trimmomatic, and poor-quality bases were corrected with Rcorrector, both using standard parameters. Quantification was performed by pseudoalignment with Kallisto v0.46.2 , with a B. germanica genome  normalization was used . This noe genome  plus the package . Figures package  and latt package  in R. In package  with sta


This study aimed to evaluate the effect of acellular dermal matrix allograft (ADMA) for the treatment of gingival recession as a substitute for subepithelial connective tissue graft (SCTG). In this controlled clinical trial, 18 teeth were selected in nine subjects with bilateral gingival recession. One side was treated with SCTG and a coronally displaced flap as the control group, and the other side was treated with ADMA and a coronally displaced flap as the test group. Probing pocket depth (PPD), clinical attachment level, vertical recession depth, recession width, gingival thickness, keratinized tissue width, and the root coverage percentage were measured before the surgery and at 1-, 3-, and 6-month postoperative intervals. The healing index, pain index, and patient satisfaction were also investigated. The data were analyzed with a general linear model (GLM) repeated measures and paired t-test. All the parameters improved except for PPD; however, a comparison between the groups did not reveal statistically significant differences. Only root coverage percentage and pain index were significantly lower in the test group. The average percentage of root coverage in the control and test groups were 82.01±16.62% and 64.44±9.4%, respectively.  Both methods resulted in improvements in the clinical results. However, the use of the ADMA led to less pain and root coverage in comparison with the SCTG method. In more than 50% of people, one or more gingival recessions with <1 mm height have been observed. The gingival recession might cause an increase in tooth sensitivity, pain, an unaesthetic appearance of the gingiva, and loss of periodontal attachment; it may also make dental healthcare difficult. Among all the factors which cause gingival recession, the most common reason is the traumatic and abrasive use of the toothbrush, which can involve the buccal surfaces of the teeth; also, gingival recession could happen as a result of inflammatory conditions, and it generally presents in patients with periodontitis.“Gingival margin situated in apical of the cementoenamel junction” has been considered as the gingival recession, which could lead to the exposure of the root surface and loss of the attached gingiva.It seems that the most important factor which increases the risk of the gingival recession is the thin gingival biotype covering the thin marginal tissue. the autogenous connective tissue graft, pedicle autografts , subepithelial connective tissue grafts (SCTG), tissue engineering techniques , and the use of biological mediators to prevent the progression of gingival recession, facilitate the plaque control, protect the keratinized gingiva, reduce the high frenum activity, and reduce tooth hypersensitivity. SCTG has the advantages of both free gingival autografts and pedicle grafts. The high survival rate of the subepithelial connective tissue graft is attributed to the existence of two blood sources, namely the facial gingival tissue flap and the exposed bed of the root zone environment. Although the subepithelial connective tissue graft is the gold standard, pain, the patient’s inconvenience, the sufficiency of the donor area, bleeding of the harvesting region, and a need for a second surgery are the complications of this method. Therefore, the acellular dermal matrix allograft has been widely applied as a substitute for autogenous tissue grafts in mucogingival surgeries. This allograft is made of human corpse skin through decellularization, freezing, and drying processes to prevent inflammation or rejection of the transplant. However, the essential factors of the tissue structure, such as collagen, elastin, proteoglycans, and vascular channels, are maintained in the process. According to the studies, due to the presence of vascular channels in the region, ADMA would be integrated with the host tissue and preserve its structural integrity.Various methods have been applied to cover the roots, including the autogenous free gingival graft,Many studies concluded that the application of ADMA is comparable to subepithelial connective tissue graft. The mean root coverage of these two methods did not show clinically significant differences.In this regard, it seems that this method could be an appropriate alternative to connective tissue grafts, especially in young and older people, and also those who are not systematically fit for intensive surgeries.Recently, this allograft has been produced in Iran by the Tissue Regeneration Corporation (TRC) under the proprietary name Cenoderm. It would be more appropriate for both the patient and clinician due to its availability and price because it is manufactured in Iran. The present study was conducted to clinically compare the acellular dermal matrix allograft (Cenoderm) and subepithelial connective tissue graft. ≤ 20%), (3) all recessions in either Miller I or II category, (4) bilateral isolated buccal gingival recession with a depth of at least 2 mm from the cementoenamel junction (CEJ) in the anterior and premolar teeth, (5) no filling and bleeding upon probing in the selected teeth (6), and adequate vestibular depth. The exclusion criteria were defined as follows: (1) pregnancy, (2) confounding medications interfering with wound healing , (3) cigarette smoking, (4) traumatic methods of brushing and application of abrasive toothpaste, (5) a history of periodontal surgery in the past two years, (6) wearing removable prostheses or orthodontic appliances in the designated area, (7) long-term  use of antibiotics in the last three months, and (8) known allergies to the materials used during periodontal surgery.Eighteen teeth were selected in nine subjects with bilateral gingival recession for this randomized, double-blind controlled, split-mouth study. The inclusion criteria were as follows: (1) ≥18 years of age, (2) ability to maintain proper oral hygiene . All the enrolled patients were provided with an oral explanation of the study, and written informed consent was obtained.This study was reviewed and approved by the Ethics Committee of Babol University of Medical Sciences and registered at The patients were treated either with subepithelial connective tissue graft and a coronally positioned flap or an acellular dermal matrix allograft with a coronally positioned flap.A 4-interval permuted block method was used to assign the patients to receive any type of intervention on the right side . The assignments were sent in closed envelopes to the clinician in charge (PH), who was unaware of the assignment codes. Further measurements of periodontal indices were performed by another clinician (NJ), who was also blinded to the study arms. All the surgeries were performed by the same clinician, and the measurements and randomization were made by another clinician.Phase I periodontal therapy was performed for all the patients. All the procedures were performed by the same person (PH). After adequate and profound local anesthesia  with 2% lidocaine containing epinephrine at a concentration of 1:80000, all the exposed roots were carefully prepared by scaling and root planing.The sulcular incision was made at the recipient site. The flap was beveled in the interdental papilla region adjacent to the tooth with the exposed root. A partial-thickness flap was raised beyond the mucogingival junction. The mesiodistal width of the incision was extended to the line angle of the adjacent teeth mesially and distally. Mesial and distal vertical releasing incisions were also made. The required graft width was measured using a periodontal probe. A connective tissue graft was prepared from the palate, measuring 1–1.5 mm in thickness and fixed at the recipient site with a 4-0 bio-absorbable polyglycolic suture. Then, a coronally repositioned flap was relocated to cover the graft and stabilized in the site with a sling suture  and 2. AA non-eugenol periodontal dressing was placed on the donor site, which was removed along with the sutures approximately two weeks later. All the patients were instructed to rinse with %0.12 chlorhexidine twice a day for four weeks. A systemic antibiotic  and a pain killer  were prescribed for a week. All these measurements were repeated one, three and six months after the periodontal surgery. In addition, the healing index (Landry’s index)  diagram. The root coverage index was obtained from the following equation: (Recession depth at baseline – Recession depth at the 6th month)/Recession depth at baseline) ×100. In all the sessions, clinical photographs were also taken.Baseline measurements were recorded using a periodontal probe, and the records were rounded to the nearest 0.5 mm using a University of Michigan “O” probe with Williams marking. The recorded indices were as follows: keratinized tissue width , clinical attachment level , probing depth , recession depth , recession width , gingival thickness  and esthetic index .s index) 36 was The subjects were recruited from patients referred to the Department of Periodontics, Dental School, Babol University of Medical Sciences, Babol, Iran. Patients with bilateral gingival recession were selected from enrolled patients and randomly recruited in the clinical trial.The sample size was estimated at nine subjects (n=9) to achieve an 80% power for a standardized difference of 1.8 between the two study arms, calculated for the primary endpoint (recession depth), using an Altman’s nomogram. Continuous data were expressed as means (±standard deviations). Kolmogorov-Smirnov test was used to assess the normal distribution of the data. The changing trend of each index within each study arm group was traced using GLM repeated measures (RM) statistics. Sphericity (one of the GLM-RM assumptions) was tested with Mauchly’s test, and the data were adjusted and reported with epsilon Greenhouse–Geisser correction in case of violation.Furthermore, a Bonferroni test was used to evaluate differences between the groups. The Friedman test was applied to trace the changing trends of nonparametric data. Moreover, the mean difference in each non-normally distributed index was calculated from the beginning to the end of the study and compared with a paired t-test. A two-tailed α at P<0.05 was considered statistically significant.0 were compared between the two groups to figure out any possible confounding effect due to the baseline differences. The t-test showed no significant difference in any of the indices (P<0.05).Baseline indices of the patients at T2(3)=10.05, P=0.02)], others improved, including recession depth (F(1.94)=84.15, P<0.001), recession width (F(1.93)=77.93, P<0.001), the width of keratinized gingiva (F(1.66)=37.84, P<0.001), clinical attachment level (F(1.84)= 45.04, P<0.001), pain (F(2)=83.78, P<0.001), thickness of keratinized gingiva , healing index , and esthetic .Changing trends of measured indices were all statistically significant, as shown in In intergroup comparisons, patients in the SCTG group reported greater pain  and displayed better root coverage . Meanwhile, other indices were not in contrast with the study groups: esthetic improvement , improved healing , increased thickness of attached gingiva , probing depth change , improved clinical attachment level , gained width of keratinized gingiva , improved recession depth  and improved recession depth   and 7.In this research, CAF + Cenoderm (test group) was compared with CAF + SCTG (control group) for the treatment of Miller class I/ll buccal gingival recession. Barros et al, Bouchard et al, and Agarwal et al, which were expected because the subepithelial connective tissue graft is a gold standard method.No significant difference was observed between the two groups in any of the parameters at baseline. The average percentage of root coverage in the Cenoderm group was significantly less than that in the SCTG group , consistent with the findings reported by Novaes et al, Haghighati et al, Hirsch et al, and Juluri et al.In the present study, the average clinical attachment gain improved in both groups, with no significant difference between them, consistent with the result of the studies by Novaes et al, but not all of them. These differences in PPD values could be attributed to the variations in the initial PPD and differences in examiners.The changes in probing depth were not significant in the two groups, indicating that PPD did not change during the study, consistent with several previous studies the use of SCTG leads to more gains in the keratinized gingiva compared to ADMA. They believed that this is because ADMA needs more time for keratinization of the epithelial surface. However, a study by Novaes et al was consistent with this study, which showed an increase in the keratinized tissue width in both methods (SCTG and ADMA) after six months, with no significant difference between them.According to Gholami et al, Rahmani et al, Gholami et al, and Shori et al.The mean average of depth and width reduction of gingival loss was enhanced in both groups, with no significant difference between them, consistent with the results reported by Novaes et al,Despite the difference in the amount of coverage between the two groups, there was no difference between these two treatment methods in terms of the VAS index for esthetic.An assessment of tissue repair was carried out by Landry index in each group, which showed an improvement, with no significant difference between the two groups.The indices of healing, esthetic, and pain have not been investigated in other studies. These results could be considered as one of the advantages of the ADMA method.The gingival thickness, too, improved in both groups, with no significant difference between them. VAS for pain showed an apparent difference between the two groups. The pain was considerably less severe in the test group in comparison with the control group. These results were somehow predictable because the surgical site was more extensive with the SCTG technique compared to the ADMA technique. According to this study, patients used more analgesics for a longer duration.Furthermore, it is possible to treat a broader region in this technique in comparison with the other techniques, such as SCTG. The advantage of fewer complications of ADMA (Cenoderm) could be exploited in young people under orthodontic treatments and older people with systemic problems, especially those with bleeding disorders.According to the results of this study, both SCTG and Cenoderm resulted in improvements in the clinical outcomes. However, the use of Cenoderm led to less severe pain and less root coverage in comparison with the SCTG technique.NJ: Executor, MY: Executor, PHA: Executor and corresponding author, AB: Statistics Consultant. All authors have read and approved the final manuscript.http://www.irct.ir .The study protocol was approved by the Ethical Committee of Babol University of Medical Sciences and registered at Yes- Cenoderm (Tissue Regeneration Corporation).


Orphans and vulnerable children (OVC) are a high-risk group for HIV infection, particularly in Sub-Saharan Africa.This study aims to portray the socioeconomic profile of OVC and examine the association of household and parent/guardian characteristics with the HIV status of OVC.For this quantitative retrospective study, we obtained data from ICAP/DRC for a total of 1,624 OVC from households enrolled for social, financial, and clinical services between January 2017 and April 2020 in two provinces of the Democratic Republic of Congo, Haut-Katanga and Kinshasa. We computed descriptive statistics for OVC and their parents' or guardians' characteristics. We used the chi-square test to determine bivariate associations of the predictor variables with the dichotomous dependent variable, HIV positivity status. To analyze the association between these independent variables and the dichotomous dependent variable HIV status after controlling for other covariates, we performed firth's logistic regression.Of the OVC included in this study, 18% were orphans, and 10.9% were HIV+. The chi-square analysis showed that among parents/guardians that were HIV+, a significantly lower proportion of OVC (11.7%) were HIV+ rather than HIV- (26.3%). In contrast, for parents/guardians with HIV- status, 9.0% of OVC were HIV-negative, and 11.7% of OVC were OVC+. The firth's logistic regression also showed the adjusted odds of HIV+ status were significantly lower for OVC with parents/guardians having HIV+ status themselves  compared with HIV-negative parents/guardians. The adjusted odds of HIV+ status were significantly lower for OVC with a monthly household income of < $30  compared with OVC with a monthly household income > $30.Our results suggest that, with the exception of a few household and parent/guardian characteristics, the risk of HIV+ status is prevalent across all groups of OVC within this study, which is consistent with the existing body of evidence showing that OVC are in general vulnerable to HIV infection. With a notable proportion of children who are single or double orphans in DRC, HIV+ OVC constitute a high-risk group that merits customized HIV services. The findings of this study provide data-driven scientific evidence to guide such customization of HIV services. Human immunodeficiency virus (HIV) infection control programs need scientific evidence on HIV risk factors in vulnerable populations such as orphans and vulnerable children (OVC) to eliminate new HIV infections and to customize HIV prevention, treatment, and management services . Public The HIV epidemic continues to be a global health problem, specifically in resource-limited countries in Sub-Saharan Africa, such as the DRC. This remains particularly true for pediatric HIV patients, some of whom are OVC; over 90 percent of all pediatric HIV patients reside in Sub-Saharan Africa . PEPFAR/Vulnerability and other factors such as orphan status, isolation and stress, social stigma, and hardship are detrimental to OVC's physical and emotional health  and incrParents and caregivers significantly impact children's and youths' treatment adherence . In theiThe DRC's HIV+ OVC face the same challenges as those in other resource-limited Sub-Saharan countries. Currently, over 700,000 children in the DRC have been left orphaned due to HIV . With thn = 175), and Kinshasa . This study focused on OVC as the non-OVC data were unavailable in this database. Per PEPFAR definitions, the age range for OVC is from 0 to 17 years. The source of the OVC dataset was household records, created from several different household files linked through household identification numbers. The data for these files came from household members' screening and assessment for eligibility and enrollment in various social, financial, and clinical services and from the monitoring of each household beneficiary's services. Household eligibility was assessed based on the presence of one or more of the following: (a) HIV+ children/adolescents newly started on ART, (b) HIV+ children or adolescents suspected of treatment failure, (c) children exposed to HIV who were <2 years of age, (d) children or adolescents living with an HIV+ adult at an advanced stage of the disease, and (e) high-risk teenage girls. High-risk teenage girls have an older sex partner, multiple sex partners, and/or adolescent sex workers. This high-risk group also included sexually exploited or abused adolescent girls. This dataset included both male and female OVC enrolled in the system, regardless of HIV status. HIV+ children who have already been on ART and had no treatment failure were not included in this database per the HIV program decision.Based on secondary data, this quantitative retrospective study analyzed de-identified individual-level programmatic records obtained from ICAP/DRC for 1,624 OVC enrolled between January 2017 and April 2020 in two provinces of the Democratic Republic of Congo, Haut-Katanga  and HIV+ (coded as 1). The proportion of OVC for whom the HIV status was not declared was relatively small in the final dataset , so they were excluded from the multivariable analyses. To ascertain the extent to which this exclusion may have caused any bias, we used the chi-square to see if those with HIV status declared vs. undeclared differed by OVC characteristics. There were small though statistically non-significant differences by age and sex; the differences were statistically significant by urban health zones and formal schooling.age at the time of enrollment was computed by calculating the difference between the date of birth and the date of enrollment and subsequently grouped into four categories: <5 years, 5 to <10 years, 10 to < 15 years, and 15 years or older. A child's sex was a dichotomous variable with attributes of both males and females. Whether the child is in school and the child's handicap status were both dichotomous variables with yes and no categories, as noted in the casework database.Three sets of independent variables were included in the analysis. The first set consisted of child characteristics. The OVC main source of drinking water originally had three categories – (a) private hand pumps, (b) public taps, drilling, rainwater, well/protected source, and catchment scheme, and (c) river, stream, lake, pond, well, or unprotected spring. This variable was coded as dichotomy by combining (a) and (b) above. Toilet type was a dichotomous variable with “no toilet/latrine” and “toilet with or without flush” as two attributes. The household having a monthly income of < $30 was recorded as yes or no. Both variables, sex of the parent/guardian and parent's/guardian's HIV status, were dichotomous with the attributes of male or female and HIV-negative or HIV+, respectively. The variable age of the parent/guardian was coded as <40 years of age, 40–49 years of age, 50 years or older, and not reported. The third set of characteristics consisted of facility characteristics, one of which was included in the analysis, the rurality or urbanicity of the health zone, coded as “rural or semi-rural” and “urban”.The second set of independent variables comprised guardian/parent and household characteristics. The p-value of 0.05 or lower to determine statistical significance. To examine the association between these independent variables and the dichotomous dependent variable HIV status after controlling for other covariates, we performed firth's logistic (FL) regression to compute three separate FL models, first for the OVC characteristics as covariates, the second with parent/guardian or household socioeconomic characteristics, and the third one for the facility characteristics. Firth's logistic regression was deemed appropriate to reduce bias in the estimation of maximum likelihood (ML) coefficients resulting from small samples or extremely disproportionate binary outcomes  resulting from extremely disproportionate attribute distribution of the outcome variable—HIV status   . Puhr et38 HIV-) . We perf38 HIV-) . GeorgiaOrphans constituted 18% of the OVC included in this study . One-in-Most OVC (87.2%) had access to water sources comprising public taps, drilling, rainwater, wells, or other protected sources, whereas the remaining 12.8% had another source of water such as a river, stream, lake, pond, well, or unprotected spring. The majority of OVC had a toilet with or latrine without a flush/pit toilet (62.4%), whereas 3.1% had no toilet in their homes. The majority (62.3%) of OVC households had a monthly income of <$30, whereas 3.2% had a monthly income of $30 or more; for the remaining 34.5%, the household income was unknown. Forty-three percent of the parents/guardians were female, 20.3% were male, and 37.0 had no documented sex.One-in-four parents or current guardians were HIV+, a small proportion  were HIV-, and for the remaining 66.4%, their HIV status was not reported. A majority (87.7%) lived in an urban health zone, whereas the remaining 12.3% were in rural or semi-rural health zones. The mean age of the parents or guardians was 44.6 years. The age distribution of the parents or guardians showed that 20.8% were <40 years of age, 21.4% were 40–49 years of age, 20.4% were 50 years old or older, and the remaining 37.4% did not have their age documented. The stratification of these characteristics is shown in P < 0.001). There was no significant statistical difference in HIV status among OVC regardless of household socioeconomic characteristics such as type of toilet, monthly household income below $30, or the source of drinking water. The risk of HIV was no different across OVC by different parent/guardian characteristics such as age or sex. However, significant variation (P < 0.001) in OVC's HIV status was observed in parents/guardians' own HIV status. Among parents/guardians that were HIV+, a significantly lower proportion of OVC (11.7%) were HIV+ rather than HIV-negative (26.3%). In contrast, for parents/guardians with HIV- status, 11.7% of OVC were HIV+, and 9.0% of OVC were HIV-. For parents with unknown  HIV status, 64.7% of OVC were HIV-, and 76.7% of OVC were OVC+.Bivariate associations tested with chi-square statistics, depicted in For further assessment of the associations based on chi-square tests, the results of firth's logistic regression are presented in The odds of HIV+ status were significantly lower for OVC with a monthly household income of < $30  compared with OVC with a monthly household income of > $30, after controlling for other households and parent/guardian characteristics. The adjusted odds of HIV+ status were also significantly lower for OVC with HIV+ parents/guardians  compared with HIV-negative parents/guardians. The odds of HIV+ status were significantly lower for OVC in urban areas  compared to OVC in rural and semi-rural areas.HIV/AIDS prevention, care, and treatment programs rely heavily on empirical evidence to improve the quality and effectiveness of their services. To contribute to such critically needed research evidence for HIV/AIDS programs in the DRC, we, in the current study, focused on analyzing individual-level programmatic data about OVC enrolled in an HIV/AIDS program based on various criteria. The data were from clinics supported by the Centers for Disease Control and Prevention (CDC) with President's Emergency Plan for AIDS Relief (PEPFAR) funding in Haut-Katanga and Kinshasa provinces. Although the national strategic plan for the response to AIDS has always taken OVC into account and underlined its importance in several strategic areas, this study sheds light on OVC's HIV status and associated factors, providing critical practice-relevant evidence.Our study results show that orphans constituted 18% of the OVC included in this study, of which 10.9% were HIV+. Having an orphan or a child who is not the biological child of the household head in one's home is quite prevalent in the DRC. A national survey from 2013–2014 showed that in the general population, 25% of households had children under 18 years of age who lived without their parents, and 12% of the households had single orphans (one parent deceased), whereas 2.4% of the households had double orphans (both parents deceased) .These OVC are truly vulnerable as they are in poor socioeconomic conditions, with 1,012 of the 1,064 or 95% living with a household income of one dollar a day or less. This is extreme poverty relative to the international poverty line set at $1.90 daily . These OIt is unclear why being in school was higher for OVC HIV+ 30.7%) vs. OVC HIV-negative 9.1%). This uncertainty about school enrollment may have been because 80% of the OVC in the database were referrals by healthcare workers because they lived in a household with one or more HIV+ adults; therefore, when someone other than the parent/guardian is reporting on the child's behalf, they may not know their school enrollment status. Household vulnerability and school dropouts would contribute to low school enrollment. These analyses revealed no variation in the proportion of HIV+ OVC by other characteristics such as age and sex, indicating that OVC of all ages and both sexes needed equal attention. Our findings of the higher proportion of HIV-negative OVC in the parent/guardian group that were themselves HIV+ are noteworthy, and several explanations can be proposed as follows: %. This u When ext0.7% vs. The study has some limitations; thus, our findings should be interpreted with those in mind. First, the OVC in the study did not represent all OVC found in the general population in the DRC. Instead, the enrollment with HIV clinics in Haut-Katanga and Kinshasa provinces occurred through multiple entry modes, with 8 out of 10 enrolled because the community-level caseworkers had enrolled an HIV+ adult in the same households. So, the findings may not be generalizable to similar OVC populations. Second, data were not always collected about the OVC from the person most knowledgeable. Third, some variables had a large proportion of cases with missing data, so those variables could not be included as covariates in the statistical model. Fourth, the study utilized a retrospective design, so disaggregation desirable by additional socioeconomic characteristics and type of orphan  was not available. Fifth, there is a potential for a household clustering effect due to some cases of multiple children coming from the same households. However, the secondary data did not include a family-level identifier, which would enable us to make that determination. Finally, many of the OVC and guardian characteristics were unreported, perhaps due to social desirability and social stigma associated with those attributes . Regardless of these limitations, the study makes an important contribution in that it is the first of its kind in the DRC, and the findings are important for targeted and efficient interventions for OVC. We have included interpretation of non-significant results for variables that are traditionally seen as very important variables in HIV patient research. When there is no statistically significant difference among one or more of these variables, the authors feel that it is important to report these. It allows other researchers to recognize that a patient's status can be impacted regardless of patient characteristics such as age or sex.Given the persisting HIV epidemic in Sub-Saharan countries, targeted, data-driven efforts to inform HIV prevention, care, and treatment programs are imperative, particularly in resource-poor countries such as the DRC. The current study describes the profile of OVC in Haut-Katanga and Kinshasa provinces, showing that OVC is a high-risk subgroup that may merit customized and targeted interventions. A notable proportion of these children were HIV+, many of whom may be orphans, and an abnormally high proportion was not in school. OVC whose school enrollment status was unknown were at a greater risk of being HIV+ than other OVC, implying that their enrollment may be unstable due to HIV. Age and sex of OVC were not significantly associated with elevated odds of being HIV+, suggesting that younger age is not as dominant an aspect of vulnerability to HIV infection as the orphan status . We alsoLMaluantesa@fhi360.org.The data analyzed in this study is subject to the following licenses/restrictions: The program-implementing partners required that data be destroyed after publication. The authors do have data until the publication of the article. The authors can facilitate data access if requested with proper permission from the DRC Ministry of Health. Requests to access these datasets should be directed to Lievain Maluantesa, The studies involving human participants were reviewed and approved by Georgia Southern University's Institutional Review Board approved the study under project protocol number H l9260. Written informed consent from the participants' legal guardian/next of kin was not required to participate in this study in accordance with the national legislation and the institutional requirements.Conceptualization: GS, GE, LM, KW, EE, BB, AM, AT, and OI. Methodology: GS, GE, and LM. Formal analysis: GS and KW. Investigation: GS. Writing—original draft preparation: GS, LM, GE, and KW. Writing—review and editing: GS, GE, LM, KW, EE, AM, OI, AT, BB, and AM. Supervision and funding acquisition: GS. Project administration: GS and LM. All authors made substantial contributions to this manuscript, with the following areas of specific contributions and have read and agreed to the published version of this manuscript.This research was supported by the President's Emergency Plan for AIDS Relief (PEPFAR) through the Centers for Disease Control and Prevention (CDC) under the terms of grant number 5 NU2GGH002033-02-00. The findings and conclusions in this journal article are those of the authors and do not necessarily represent the official position of the funding agencies.Author GE was employed by the organization FHI. Authors LM, EE, and AM were employed by the organization FHI 360. The remaining 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.