Vertebral and Femoral Bone Mineral Density (BMD) Assessment with Dual-Energy CT versus DXA Scan in Postmenopausal Females.

This study aimed to demonstrate the potential role of dual-energy CT in assessing bone mineral density (BMD) using hydroxyapatite-fat material pairing in postmenopausal women. A retrospective study was conducted on 51 postmenopausal female patients who underwent DXA and DECT examinations for other clinical reasons. DECT images were acquired with spectral imaging using a 256-slice system. These images were processed and visualized using a HAP-fat material pair. Statistical analysis was performed using the Bland-Altman method to assess the agreement between DXA and DECT HAP-fat measurements. Mean BMD, vertebral, and femoral T-scores were obtained. For vertebral analysis, the Bland-Altman plot showed an inverse correlation (R2: -0.042; RMSE: 0.690) between T-scores and DECT HAP-fat values for measurements from L1 to L4, while a good linear correlation (R2: 0.341; RMSE: 0.589) was found for measurements at the femoral neck. In conclusion, we demonstrate the enhanced importance of BMD calculation through DECT, finding a statistically significant correlation only at the femoral neck where BMD results do not seem to be influenced by the overlap of the measurements on cortical and trabecular bone. This outcome could be beneficial in the future by reducing radiation exposure for patients already undergoing follow-up for chronic conditions.

Effect of Fabrication Technology on the Accuracy of Surgical Guides for Dental-Implant Surgery.

BACKGROUND: The accuracy of surgical guides is a relevant factor in both surgical safety and prosthetic implications. The impact of widespread fabrication technologies (milling and 3D printing) was investigated. METHODS: Surgical guides manufactured by means of two specific milling and 3D-printing systems were digitized and compared in a 3D analysis with the digital file of the designed guides. The surface mean 3D distance (at the surface where the teeth and mucosa made contact) and the axial and linear deviations of the sleeves' housings were measured by means of a metrological software program. Univariate and multivariate statistical analyses were used to investigate the effects of the fabrication technology, type of support, and arch type on the surgical guides' accuracy. RESULTS: The median deviations of the intaglio surface in contact with the mucosa were significantly (p < 0.001) lower for the milled surgical guides (0.05 mm) than for the 3D-printed guides (-0.07 mm), in comparison with the reference STL file. The generalized estimated equation models showed that the axial deviations of the sleeves' housings (a median of 0.82 degrees for the milling, and 1.37 degrees for the 3D printing) were significantly affected by the fabrication technology (p = 0.011) (the milling exhibited better results), the type of support (p < 0.001), and the combined effect of the fabrication technology and the sleeve-to-crest angle (p = 0.003). The linear deviation (medians of 0.12 mm for the milling and 0.21 mm for the 3D printing) of their center points was significantly affected by the type of support (p = 0.001), with the milling performing slightly better than the 3D printing. CONCLUSIONS: The magnitude of the difference might account for a limited clinical significance.

Artificial Intelligence for Personalized Genetics and New Drug Development: Benefits and Cautions.

As the global health care system grapples with steadily rising costs, increasing numbers of admissions, and the chronic defection of doctors and nurses from the profession, appropriate measures need to be put in place to reverse this course before it is too late [...].

Machine Learning and BMI Improve the Prognostic Value of GAP Index in Treated IPF Patients.

Patients affected by idiopathic pulmonary fibrosis (IPF) have a high mortality rate in the first 2-5 years from diagnosis. It is therefore necessary to identify a prognostic indicator that can guide the care process. The Gender-Age-Physiology (GAP) index and staging system is an easy-to-calculate prediction tool, widely validated, and largely used in clinical practice to estimate the risk of mortality of IPF patients at 1-3 years. In our study, we analyzed the GAP index through machine learning to assess any improvement in its predictive power in a large cohort of IPF patients treated either with pirfenidone or nintedanib. In addition, we evaluated this event through the integration of additional parameters. As previously reported by Y. Suzuki et al., our data show that inclusion of body mass index (BMI) is the best strategy to reinforce the GAP performance in IPF patients under treatment with currently available anti-fibrotic drugs.

Different Expression of Micro-RNA in the Subcutaneous and Visceral Adipose Tissue of Obese Subjects.

Obesity is a pathology characterized by an excessive accumulation of adipose tissue and it is a condition associated with complex alterations affecting different organs and systems. Obesity has great influences on cardiovascular and respiratory morbidity and mortality, and impairs the multiple aspects of metabolism. Since micro-RNAs (miRNAs) are thought to play a role in the regulation of various pathological processes, in this complex framework, the investigation of these classes of noncoding regulatory RNA seems to be promising. Selected group of obese subjects was recruited. We analyzed the expression of seven miRNAs from obese adipose tissue supposed to have a role in the pathogenesis of cardiovascular and respiratory disease related to obesity and we compared it with the expression of the same miRNAs in a group of nonobese controls. In this study what emerged is miR-27b and miR-483 significant downregulation in subcutaneous adipose tissue from obese group compared with nonobese ones. For visceral adipose tissue, a significant decrease in miR-27b and miR-223 expression was observed in obese group. Moreover, a different expression of miR-26a and miR-338 in the obese group was found. Those findings could help the individuation of previously unknown key players in the development of different diseases usually associated with obesity, such as cardiovascular and pulmonary diseases. Clinical Trials.gov ID: Ref 17/CE/2014.

Machine learning and predictive models: 2 years of Sars-CoV-2 pandemic in a single-center retrospective analysis.

BACKGROUND: Since January 2020, coronavirus disease 19 (COVID-19) has rapidly spread all over the world. An early assessment of illness severity is crucial for the stratification of patients in order to address them to the right intensity path of care. We performed an analysis on a large cohort of COVID-19 patients (n=581) hospitalized between March 2020 and May 2021 in our intensive care unit (ICU) at Policlinico Riuniti di Foggia hospital. Through an integration of the scores, demographic data, clinical history, laboratory findings, respiratory parameters, a correlation analysis, and the use of machine learning our study aimed to develop a model to predict the main outcome. METHODS: We deemed eligible for analysis all adult patients (age >18 years old) admitted to our department. We excluded all the patients with an ICU length of stay inferior to 24 h and the ones that declined to participate in our data collection. We collected demographic data, medical history, D-dimers, NEWS2, and MEWS scores on ICU admission and on ED admission, PaO2/FiO2 ratio on ICU admission, and the respiratory support modalities before the orotracheal intubation and the intubation timing (early vs late with a 48-h hospital length of stay cutoff). We further collected the ICU and hospital lengths of stay expressed in days of hospitalization, hospital location (high dependency unit, HDU, ED), and length of stay before and after ICU admission; the in-hospital mortality; and the in-ICU mortality. We performed univariate, bivariate, and multivariate statistical analyses. RESULTS: SARS-CoV-2 mortality was positively correlated to age, length of stay in HDU, MEWS, and NEWS2 on ICU admission, D-dimer value on ICU admission, early orotracheal intubation, and late orotracheal intubation. We found a negative correlation between the PaO2/FiO2 ratio on ICU admission and NIV. No significant correlations with sex, obesity, arterial hypertension, chronic obstructive pulmonary disease, chronic kidney disease, cardiovascular disease, diabetes mellitus, dyslipidemia, and neither MEWS nor NEWS on ED admission were observed. Considering all the pre-ICU variables, none of the machine learning algorithms performed well in developing a prediction model accurate enough to predict the outcome although a secondary multivariate analysis focused on the ventilation modalities and the main outcome confirmed how the choice of the right ventilatory support with the right timing is crucial. CONCLUSION: In our cohort of COVID patients, the choice of the right ventilatory support at the right time has been crucial, severity scores, and clinical judgment gave support in identifying patients at risk of developing a severe disease, comorbidities showed a lower weight than expected considering the main outcome, and machine learning method integration could be a fundamental statistical tool in the comprehensive evaluation of such complex diseases.

Trueness of Intaglio Surface of Milled Digital Dentures Designed from Intraoral Scans.

PURPOSE: To asses trueness of the intaglio surface of milled dentures fabricated according to a fully digital protocol starting from intraoral scans in a clinical study by means of 3-dimensional (3D) digital analysis. MATERIALS AND METHODS: Ten maxillary and 10 mandibular dentures, designed from intraoral scans and milled in-house, were studied. Intraoral scans were compared with the scans of intaglio surface of milled dentures. To this end, they were aligned, trimmed and used in a metrology software to measure their mean 3D distance, absolute mean deviation, and other parameters. Measured differences for all parameters were statistically investigated. Subgroup analysis for the maxillary and mandibular dentures was performed using independent samples t-test or, in case of non-normal distribution, by means of Mann-Whitney test. RESULTS: Using a mean of 24.9 ±2.8 measurement points/mm2 , a mean 3D distance of 0.0006 ±0.007 mm between intraoral scans and the scans of the intaglio surface of milled dentures was measured. The corresponding absolute mean deviation was 0.055 ±0.032 for maxillary dentures and 0.061 ±0.016 for mandibular dentures; such a difference between arches was statistically significant (p = 0.035). CONCLUSIONS: Milled dentures fabricated using a fully digital protocol and intraoral scans have accurate intaglio surfaces. It is reasonable to assume that they may achieve an adequate fit.

Machine learning-based prediction of adherence to continuous positive airway pressure (CPAP) in obstructive sleep apnea (OSA).

Continuous positive airway pressure (CPAP) is the "gold-standard" therapy for obstructive sleep apnea (OSA), but the main problem is the poor adherence. Therefore, we have searched for the causes of poor adherence to CPAP therapy by applying predictive machine learning (ML) methods. The study was conducted on OSAs in nighttime therapy with CPAP. An outpatient follow-up was planned at 3, 6, 12 months. We collected several parameters at the baseline visit and after dividing all patients into two groups (Adherent and Non-adherent) according to therapy adherence, we compared them. Statistical differences between the two groups were not found according to baseline characteristics, except gender (P< .01). Therefore, we applied ML to predict CPAP adherence, and these predictive models showed an accuracy and sensitivity of 68.6% and an AUC (area under the curve) of 72.9% through the SVM (support vector machine) classification method. The identification of factors predictive of long-term CPAP adherence is complex, but our proof of concept seems to demonstrate the utility of ML to identify subjects poorly adherent to therapy. Therefore, application of these models to larger samples could aid in the careful identification of these subjects and result in important savings in healthcare spending.

Efficacy and Safety of Remdesivir over Two Waves of the SARS-CoV-2 Pandemic.

The aim of this study is to describe the features, the outcomes, and the clinical issues related to Remdesivir administration of a cohort of 220 patients (pts) with COVID-19 hospitalized throughout the last two pandemic waves in Italy. One hundred and nine pts were enrolled from 1 September 2020, to 28 February 2021 (Group A) and 111 from 1 March to 30 September 2021 (Group B). Notably, no differences were reported between the two groups neither in the timing of hospitalization. nor in the timing of Remdesivir administration from symptoms onset. Remarkably, a higher proportion of pts with severe COVID-19 was observed in Group B (25% vs. 10%, p < 0.001). At univariate and multivariate analysis, rather than the timing of Remdesivir administration, age, presence of coexisting conditions, D-dimers, and O2 flow at admission correlated positively to progression to non-invasive ventilation, especially for patients in Group B. However, the rate of admission in the Intensive Care Unit and/or death was comparable in the two groups (7% vs. 4%). Negligible variations in serum GOT, GPT, GGT, and eGFR levels were detected. A mean reduction in heart rate was noticed within the first three days of antiviral treatment (p < 0.001). Low rate of ICU admission, high rate of clinical recovery, and good drug safety were observed in COVID-19 patients treated with Remdesivir during two diverse pandemic waves.

Temporal profile of SARS-CoV-2 viral load in posterior nasopharyngeal samples: Analysis of 944 patients in Apulia, Italy.

OBJECTIVES: The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic has heavily impacted Italy. The government's restriction measures have attenuated the burden on hospitals. The association of high viral replication with disease severity suggests the potential for lower viral load in milder clinical presentations. METHODS: The reverse-transcription-polymerase-chain-reaction (RT-PCR) profile of 944 consecutive, non-replicate, positive retropharyngeal swabs was collected from 3 March to 8 June 2020 to investigate the temporal profile of SARS-CoV-2 viral load in the region of Capitanata, Apulia. Cycle threshold (Ct) values of 3 targets (N [nucleocapsid protein], E [envelope protein] and RdRP [RNA-dependent RNA-polymerase]) were analysed. RESULTS: The median Ct values of the 3 targets increased considerably over the study period, showing a progressive and constant weekly change. The negative detection rate of E and RdRP increased over time. These data suggest that SARS-CoV-2 viral load progressively decreased along the outbreak course. During the first epidemic peak (March and April) the viral load among patients >80-years was significantly higher than for younger subjects. However, in May this age-dependent difference disappeared, underlying viral load reduction in the elderly. CONCLUSIONS: An attenuation of viral transmission or pathogenicity during the epidemic course is suggested, likely due to restriction measures, although viral factors might also be considered.

Treatment of Cystic Fibrosis Patients Homozygous for F508del with Lumacaftor-Ivacaftor (Orkambi®) Restores Defective CFTR Channel Function in Circulating Mononuclear Cells.

The treatment of cystic fibrosis (CF) patients homozygous for the F508del mutation with Orkambi®, a combination of a corrector (lumacaftor) and a potentiator (ivacaftor) of the mutated CFTR protein, resulted in some amelioration of the respiratory function. However, a great variability in the clinical response was also observed. The aim of this study was to evaluate the response to Orkambi® in a small cohort of F508del/F508del patients (n = 14) in terms of clinical and laboratory parameters, including ex vivo CFTR activity in mononuclear cells (MNCs), during a 12-month treatment. Patients responded with an increase in percent predicted forced expiratory volume in 1 s (FEV1%) and body mass index (BMI) as well as with a decrease in white blood cell (WBC) total counts and serum C-reactive protein (CRP) levels, although not significantly. Sweat chloride and CFTR-dependent chloride efflux were found to decrease and increase, respectively, as compared with pre-therapy values. CFTR and BMI showed a statistically significant correlation during Orkambi® treatment. Clustering analysis showed that CFTR, BMI, sweat chloride, FEV1%, and WBC were strongly associated. These data support the notion that CFTR-dependent chloride efflux in MNCs should be investigated as a sensitive outcome measure of Orkambi® treatment in CF patients.

Application of machine learning to predict obstructive sleep apnea syndrome severity.

INTRODUCTION: Obstructive sleep apnea syndrome has become an important public health concern. Polysomnography is traditionally considered an established and effective diagnostic tool providing information on the severity of obstructive sleep apnea syndrome and the degree of sleep fragmentation. However, the numerous steps in the polysomnography test to diagnose obstructive sleep apnea syndrome are costly and time consuming. This study aimed to test the efficacy and clinical applicability of different machine learning methods based on demographic information and questionnaire data to predict obstructive sleep apnea syndrome severity. MATERIALS AND METHODS: We collected data about demographic characteristics, spirometry values, gas exchange (PaO2, PaCO2) and symptoms (Epworth Sleepiness Scale, snoring, etc.) of 313 patients with previous diagnosis of obstructive sleep apnea syndrome. After principal component analysis, we selected 19 variables which were used for further preprocessing and to eventually train seven types of classification models and five types of regression models to evaluate the prediction ability of obstructive sleep apnea syndrome severity, represented either by class or by apnea-hypopnea index. All models are trained with an increasing number of features and the results are validated through stratified 10-fold cross validation. RESULTS: Comparative results show the superiority of support vector machine and random forest models for classification, while support vector machine and linear regression are better suited to predict apnea-hypopnea index. Also, a limited number of features are enough to achieve the maximum predictive accuracy. The best average classification accuracy on test sets is 44.7 percent, with the same average sensitivity (recall). In only 5.7 percent of cases, a severe obstructive sleep apnea syndrome (class 4) is misclassified as mild (class 2). Regression results show a minimum achieved root mean squared error of 22.17. CONCLUSION: The problem of predicting apnea-hypopnea index or severity classes for obstructive sleep apnea syndrome is very difficult when using only data collected prior to polysomnography test. The results achieved with the available data suggest the use of machine learning methods as tools for providing patients with a priority level for polysomnography test, but they still cannot be used for automated diagnosis.

G-CSF and GM-CSF Modify Neutrophil Functions at Concentrations found in Cystic Fibrosis.

The role of colony stimulating factors (CSFs) in cystic fibrosis (CF) circulating neutrophils has not been thoroughly evaluated, considering that the neutrophil burden of lung inflammation in these subjects is very high. The aim of this study was to assess granulocyte-CSF (G-CSF) and granulocyte-macrophage-CSF (GM-CSF) levels in CF patients in various clinical conditions and how these cytokines impact on activation and priming of neutrophils. G-CSF and GM-CSF levels were measured in sputum and serum samples of stable CF patients (n = 21) and in CF patients with acute exacerbation before and after a course of antibiotic therapy (n = 19). CSFs were tested on non CF neutrophils to investigate their effects on reactive oxygen species (ROS) production, degranulation (CD66b, elastase, lactoferrin, MMP-9), and chemotaxis. At very low concentrations found in CF patients (0.005-0.1 ng/ml), both cytokines inhibited ROS production, while higher concentrations (1-5 ng/ml) exerted a stimulatory effect. While either CSF induced elastase and MMP-9 secretion, lactoferrin levels were increased only by G-CSF. Chemotaxis was inhibited by GM-CSF, but was increased by G-CSF. However, when present together at low concentrations, CSFs increased basal and fMLP-stimulated ROS production and chemotaxis. These results suggest the CSF levels that circulating neutrophils face before extravasating into the lungs of CF patients may enhance their function contributing to the airway damage.

MicroRNA expression profile during different conditions of hypoxia.

INTRODUCTION: MicroRNAs (miRNAs) are small non coding RNAs which play a role in several cellular processes. MiRNA expression is influenced by oxidative stress, inflammatory cascade and hypoxia. Effects of different types of hypoxia (intermittent and chronic) have been poorly investigated. The aim of this study was to evaluate how intermittent and chronic hypoxia influence the expression of a pool of miRNAs. RESULTS: Subjects with HI presented higher levels of miR-21, miR-23b, miR-145 and miR-210 compared to the other groups, while higher levels of miR-26 was observed in the HC group. Subjects with HCHI had lower levels of all selected miRNAs. A strong correlation was found between miR-23b and miR-210 and both correlated with PaO2, age and FEV1. MiR-145 is correlated with miR-21 but no correlations were found with other parameters. The level of miR-26a seems to be correlated only with BMI. MATERIALS AND METHODS: We used RT-PCR to detect the miRNAs expression in three different models of hypoxemia: intermittent (HI), chronic (HC) and both of them (HCHI). Expression of miRNAs was analyzed using ANOVA and post hoc analysis, moreover, Spearman correlation and Cluster analysis were applied to study the relationship between miRNAs and main clinical parameters. CONCLUSIONS: Intermittent hypoxia induces the expression of some miRNAs more than chronic hypoxia. These miRNAs may play an important role in the development of different diseases usually associated with OSA such as cardiovascular disease. In addition, mechanisms involved in cancer progression may be induced in the presence of chronic and more often intermittent hypoxia.

Effects of crown movement on periodontal biotype: a digital analysis.

Orthodontic treatment has important correlations with periodontal changes. Various mechanical and biological factors are involved in determining such changes, but anatomical and morphological variables, generally addressed as periodontal biotype, play a key role. In measurement of such modifications, digital and non-contact reverse engineering technologies may be of tremendous advantage. The aim of this study is to retrospectively evaluate, in a series of digitized dental casts, some of the parameters addressing periodontal biotype and correlate them to extent and direction of tooth movement. Pre- (T0) and post-treatment (T1) dental casts of 22 patients were scanned by 3Shape TRIOS 3® scanner. A number of variables (crown ratio, gingival margin position, gingival contour, papillae position, gingival scallop) were investigated and their variations calculated after digital measurements on single casts at T0 and T1, or after direct measurement (T1 vs T0) on the superimposition and alignment of digital models. Univariate and multivariate statistics were then performed. No significant correlation was detected between the sagittal or vertical movement of dental crown and displacement of the gingival margin. On the other hand, vestibular gingival contour resulted significantly altered by vestibular and extrusion movements. Further studies are needed to ascertain the differential effect of bone and soft tissue on such modifications. The relationship between orthodontic treatment and the periodontium overcomes the consideration of gingival recession and includes all the concepts of periodontal biotype with its characteristics. Digital technologies and non-contact reverse engineering techniques now available have the potential to allow a more precise definition of such a relationship.

Effects of Tibetan Music on Neuroendocrine and Autonomic Functions in Patients Waiting for Surgery: A Randomized, Controlled Study.

BACKGROUND: The aim of this study was to investigate the effects of listening to Tibetan music on anxiety and endocrine, autonomic, cognitive responses in patients waiting for urologic surgery. METHODS: Sixty patients waiting for surgery were enrolled to the study. They were randomized in music (M) and control (C) groups. The M group listened to a low-frequency Tibetan music for 30 min (T0-T30) through headphones, and the C group wore headphones with no sound. The State Trait Anxiety Inventory Questionnaire (STAI) Y-1 was administered at T0 and T30. Normalized low (LFnu) and high frequencies (HFnu) of heart rate variability, LF/HF ratio, and galvanic skin response (GRS) data were analyzed at T0, T10, T20, T30, and T35. The salivary α-amylase (sAA) samples were collected at T0, T35, and T45. RESULTS: In the M group, the STAI Y-1 score decreased at T30 versus baseline (p < 0.001), sAA levels decreased at T35 versus T0(p=0.004), and GSR remained unchanged. In the C group, the STAI Y-1 score remained unchanged, sAA level increased at T35 versus T0(p < 0.001), and GSR slightly increased at T35 versus baseline (p=0.359). LFnu was lower, and HFnu was significantly higher (T10-T30) in M versus C group. Mean LF/HF ratio slightly reduced in the M group. CONCLUSIONS: Our results suggest that preoperative listening to relaxing Tibetan music might be a useful strategy to manage preoperative anxiety.

Prevalence of comorbidities in patients with obstructive sleep apnea syndrome, overlap syndrome and obesity hypoventilation syndrome.

INTRODUCTION: Sleep-disordered breathing causes a burden to the sufferer, the health care system and the society. Most studies have focused on obstructive sleep apnea (OSA); however, the prevalence of comorbidities in patients affected by overlap syndrome (OS) and obesity hypoventilation syndrome (OHS) has not been carefully evaluated. STUDY OBJECTIVES: The principal aim of this study was to identify the presence of comorbidities in patients suffering from OSA, OS, OHS and the differences in three groups of patients. Another purpose was to verify if sleepiness is associated with a greater prevalence of comorbidities. METHODS: A retrospective analysis in 989 adults referred for sleep diagnostic testing to our sleep center was performed. Patients were classified in OSA (721), OS (123) and OHS (145). RESULTS: The prevalence of comorbidities was higher in patients affected by OS and was the highest in the OHS group, while the prevalence of arterial hypertension is the highest in patients affected by OS. The probability of having more than two comorbidities follows the same trend. Excessive daytime sleepiness was associated with an increased rate of arterial hypertension, diabetes mellitus and the presence of multimorbidity in each group of patients. CONCLUSIONS: The presence and the association of comorbidities seem to be higher in patients suffering from OSA, OS and OHS. Subjects suffering of OHS present a high prevalence of main diseases despite their younger age compared with others patients with SDB. Sleepiness may have a role, at least in a subset of these patients, into the development of comorbidities.

Dentoskeletal modifications in Class II deep bite malocclusion treatment with anterior bite plane functional appliance.

BACKGROUND: A treatment modality for Class II division 1 malocclusion is discussed. Orthodontic treatment of patients with deep bite and Class II malocclusion is an important challenge in clinical practice. The aim of this work is to compare the efficacy of anterior bite plane functional appliance (ABPFA) by assessing the changes in different times with untreated patients by literature. MATERIAL AND METHODS: The study group comprised 22 subjects with Class II division 1 malocclusion and hypo-divergent. Eligibility criteria for this study were: dental Class II division 1 malocclusion, hypo-divergent skeletal pattern, late mixed or permanent dentition. We analyzed with the use of stable bone structure (ASCB) at two different times: pre-treatment (T0) and post-treatment (T1) after 24 months. Inter-group differences were evaluated with paired samples t-test at the P<0.05 level. RESULTS: No statistical significant differences were found in cephalometric skeletal measurements, whereas dental parameters showed a significant different overjet, which was significantly reduced (6 mm at T0 vs. 5 mm at T1) in our series. CONCLUSIONS: In ABPFA group, the treatment effects were reduce mainly Class II malocclusion, overjet and overbite alteration. This appliance seems to suggest a significant beneficial effect in mandible displacement by reducing the counter clockwise rotation of the mandible, which is further confirmed by the almost absence of modifications of ArGoMe and SNGoMe angles. The ABPFA is particularly suitable to reduce the non-desirable dental effects represented by lower incisors pro inclination, and upper incisors retro-inclination. Key words:Orthodontics, Functional orthodontics, Class II malocclusion, Anterior bite plane functional appliance.