Recent developments of P-glycoprotein inhibitors and its structure-activity relationship (SAR) studies.

P-glycoprotein (P-gp) over-expression is a key factor in multi-drug resistance (MDR), which is a major factor in the failure of cancer treatment. P-gp inhibitors have been demonstrated to have powerful pharmacological properties and may be used as a therapeutic approach to overcome the MDR in cancer cells. Combining clinical investigations with biochemical and computational research may potentially lead to a clearer understanding of the pharmacological properties and the mechanisms of action of these P-gp inhibitors. The task of turning these discoveries into effective therapeutic candidates for a variety of malignancies, including resistant and metastatic kinds, falls on medicinal chemists. A variety of P-gp inhibitors with great potency, high selectivity, and minimal toxicity have been identified in recent years. The latest advances in drug design, characterization, structure-activity relationship (SAR) research, and modes of action of newly synthesized, powerful small molecules P-gp inhibitors over the previous ten years are highlighted in this review. P-gp transporter over-expression has been linked to MDR, therefore the development of P-gp inhibitors will expand our understanding of the processes and functions of P-gp-mediated drug efflux, which will be helpful for drug discovery and clinical cancer therapies.

Is Psychiatric Illness Associated With Risk for Postoperative Complications in the Outpatient Setting?

PURPOSE: Little is known about the association between psychiatric illness and the risk for postoperative complications following outpatient oral and maxillofacial surgery treatment. The purpose of this study was to examine the significance of the presence of psychiatric illness on postoperative complications. MATERIALS/METHODS: This was a retrospective cohort study conducted in 2018 that identified patients by searching through the University of Cincinnati's electronic health records. The predictor variable in this study is the presence of psychiatric illness and the outcome variable is the presence or absence of postoperative complications. Additional covariates such as age, race, location, procedure type, and anesthesia type were also included. Results of appropriate descriptive statistics and multivariate logistic regression were presented. Statistical significance was set at P value < .05. RESULTS: The total number of patients who underwent procedures involving local anesthetic and intravenous sedition in clinic in 2018 were 3,874, of which 1,588 were males (40.99%) and 2,286 were females (59.01%) with a mean age of 36.14 and 35.08 years, respectively. The sample consisted of White (45.87%), Black (35.34%), Hispanic/Latino (2.27%), Asians (1.60%), other races (3.33%), and 11.59% patients have missing data on race. A psychiatric diagnosis was found in 21.37% patients (n = 828). The percentage of patients with 2 or more psychiatric diagnoses was 5.78% (n = 224). The rate of postoperative was reported as 11.33%. A bivariate logistic regression analysis of postoperative complications as an outcome variable found that postoperative complications were not associated with psychiatric history (Odds ratio = 1.049, 95% confidence interval: 0.825 to 1.333, P value = .695). However, sex (P value = < .0001), surgical procedure (P value = < .0001), and anesthetic technique (P value = < .0001) had statistically significant associations with postoperative complications. Other covariates like race (P value = .5943), American Society of Anesthesiologists score (P value = .2539), location (P value = .5323), and multiple psychiatric diagnoses (P value = .7256) were not found to be significantly associated with postoperative complications. CONCLUSION: Although our study did show a higher prevalence of psychiatric illnesses in our patient population, it did not show any statistically significant correlation between psychiatric illness and postoperative complications. In addition, there were no statistically significant differences in postoperative complications between different Diagnostic and Statistical Manual of Mental Disorders classes.

Development and Validation of Novel Three-Dimensional Craniofacial Landmarks on Cone-Beam Computed Tomography Scans.

As cone-beam computed tomography (CBCT) scans become increasingly common, it is vital to have reliable 3-dimensional (3D) landmarks for quantitative analysis of craniofacial skeletal morphology. While some studies have developed and used 3D landmarks, these landmark sets are generally small and derived primarily from previous 2-dimensional (2D) cephalometric landmarks. These derived landmarks lack information in parts of the skull such as the cranial base, which is an important feature for cranial growth and development. The authors see a real need for development and validation of 3D landmarks, particularly bilateral landmarks, across the skull for improved cephalometric analysis. The primary objective of this study is to develop and validate a set of 61 3D anatomical landmarks on the face, cranial base, mandible, and teeth for use in clinical and research studies involving CBCT imaging. Each landmark was placed 3 times by 3 separate trained observers on a set of 10 anonymized CBCT patient scans. Intra-rater and inter-rater estimates of consistency and agreement were calculated using the intraclass correlation coefficient. Measurement error was calculated per landmark and per X, Y, and Z landmark coordinate. The authors had high ICC estimates within rates, indicating high consistency, and high ICC estimates among raters, indicate good agreement across raters. Overall measurement error for each landmark and each X, Y, and Z coordinate was low. Our results confirm the accuracy of novel 3D landmarks including several on the cranial base that will serve researchers and clinicians for use in future studies involving 3D CBCT imaging and craniofacial development.

First-order optical spatial differentiator based on a guided-mode resonant grating.

We present an experimental demonstration of a subwavelength diffraction grating performing first-order differentiation of the transverse profile of an incident optical beam with respect to a spatial variable. The experimental results are in a good agreement with the presented analytical model suggesting that the differentiation is performed in transmission at oblique incidence and is associated with the guided-mode resonance of the grating. According to this model, the transfer function of the grating in the vicinity of the resonance is close to the transfer function of an exact differentiator. We confirm this by estimating the transfer function of the fabricated structure on the basis of the measured profiles of the incident and transmitted beams. The considered structure may find application in the design of new photonic devices for beam shaping, optical information processing, and analog optical computing.

Three-Dimensional Cephalometric Landmark Annotation Demonstration on Human Cone Beam Computed Tomography Scans.

Craniofacial cephalometric analysis is a diagnostic tool used for the assessment of the relationship of various bones and soft tissues in the head and face. Cephalometric analysis has been traditionally conducted with the use of 2D radiographs and landmark sets and restricted to size, linear and angular measurements, and 2D relationships. The increasing use of 3D cone beam computed tomography (CBCT) scans in the dental field dictates the need for the evolution to 3D cephalometric analysis, which incorporates shape and a more realistic analysis of longitudinal development in all three planes. This study is a demonstration of 3D cephalometric analysis with the use of a validated set of skeletal tissue landmarks on human CBCT scans. Detailed instructions for the annotation of each landmark on a 3D volume are provided as part of a step-by-step protocol. The generated measurements and 3D coordinates of the landmarks can be exported and used both for clinical and research purposes. The introduction of 3D cephalometric analysis in basic and clinical craniofacial studies will lead to future advancements in the field of craniofacial growth and development.

Relational reasoning network for anatomical landmarking.

Purpose: We perform anatomical landmarking for craniomaxillofacial (CMF) bones without explicitly segmenting them. Toward this, we propose a simple, yet efficient, deep network architecture, called relational reasoning network (RRN), to accurately learn the local and the global relations among the landmarks in CMF bones; specifically, mandible, maxilla, and nasal bones. Approach: The proposed RRN works in an end-to-end manner, utilizing learned relations of the landmarks based on dense-block units. For a given few landmarks as input, RRN treats the landmarking process similar to a data imputation problem where predicted landmarks are considered missing. Results: We applied RRN to cone-beam computed tomography scans obtained from 250 patients. With a fourfold cross-validation technique, we obtained an average root mean squared error of < 2 mm per landmark. Our proposed RRN has revealed unique relationships among the landmarks that help us in inferring informativeness of the landmark points. The proposed system identifies the missing landmark locations accurately even when severe pathology or deformations are present in the bones. Conclusions: Accurately identifying anatomical landmarks is a crucial step in deformation analysis and surgical planning for CMF surgeries. Achieving this goal without the need for explicit bone segmentation addresses a major limitation of segmentation-based approaches, where segmentation failure (as often is the case in bones with severe pathology or deformation) could easily lead to incorrect landmarking. To the best of our knowledge, this is the first-of-its-kind algorithm finding anatomical relations of the objects using deep learning.

A prospective longitudinal study of clinical outcome and quality of life assessment in patients with chronic rhinosinusitis after functional endoscopic sinus surgery using sino nasal outcome test-22.

Chronic rhinosinusitis (CRS) significantly affect the quality of life (QoL) of patients. The study was conducted in CRS patients who were treated with functional endoscopic sinus surgery (FESS) after failure of medical treatment to analyze clinical outcome using prospectively collected data through a symptom-based rhinosinusitis outcome measure, the Sino-nasal Outcome Test-22 (SNOT-22). The aim of the study was to evaluate and compare the QoL in patients of chronic rhinosinusitis pre-operative and after FESS by SNOT-22. The prospective study was conducted on 40 patients of chronic rhinosinusitis with or without nasal polyposis. Demographic, clinical, diagnostic nasal endoscopy and radiological findings were recorded. Visual analogue scoring and SNOT-22 questionnaire scoring were done preoperatively and at 3rd and 6th months post-operatively. These scores were compared and a value of p < 0.01 was considered statistical significant. Nasal obstruction (80%) was the most commonly reported disabling condition followed by rhinorrhea (75%), facial pain-pressure (72.5%), headache and sneezing. The mean preoperative nasal endoscopy score was 8.08 ± 3.65. The mean preoperative Lund Mackay CT scan score was 11.725 ± 3.64. The mean preoperative SNOT-22 score was 46.25 ± 20.44. After FESS, nasal discharge was improved in 86% patients. Average VAS scores showed significant postoperative improvement at 6 months (p < 0.01). The mean postoperative diagnostic nasal endoscopy score improved to 2.80 ± 1.64 at 6 months (p < 0.01). The mean postoperative SNOT-22 scores decreased at postoperative follow up visits at 3 and 6 months to 14.58 ± 4.90 at 3 months and 22.38 ±7.93 at 6 months (p < 0.01). CRS patient refractory to medical treatment showed statistical significant improvement after FESS. The SNOT-22 scoring was easy to use scoring used for QoL assessment showed significant improvement after FESS.

Craniofacial Analysis May Indicate Co-Occurrence of Skeletal Malocclusions and Associated Risks in Development of Cleft Lip and Palate.

Non-syndromic orofacial clefts encompass a range of morphological changes affecting the oral cavity and the craniofacial skeleton, of which the genetic and epigenetic etiologic factors remain largely unknown. The objective of this study is to explore the contribution of underlying dentofacial deformities (also known as skeletal malocclusions) in the craniofacial morphology of non-syndromic cleft lip and palate patients (nsCLP). For that purpose, geometric morphometric analysis was performed using full skull cone beam computed tomography (CBCT) images of patients with nsCLP (n = 30), normocephalic controls (n = 60), as well as to sex- and ethnicity- matched patients with an equivalent dentofacial deformity (n = 30). Our outcome measures were shape differences among the groups quantified via principal component analysis and associated principal component loadings, as well as mean shape differences quantified via a Procrustes distance among groups. According to our results, despite the shape differences among all three groups, the nsCLP group shares many morphological similarities in the maxilla and mandible with the dentofacial deformity group. Therefore, the dentoskeletal phenotype in nsCLP could be the result of the cleft and the coexisting dentofacial deformity and not simply the impact of the cleft.

Deep Geodesic Learning for Segmentation and Anatomical Landmarking.

In this paper, we propose a novel deep learning framework for anatomy segmentation and automatic landmarking. Specifically, we focus on the challenging problem of mandible segmentation from cone-beam computed tomography (CBCT) scans and identification of 9 anatomical landmarks of the mandible on the geodesic space. The overall approach employs three inter-related steps. In the first step, we propose a deep neural network architecture with carefully designed regularization, and network hyper-parameters to perform image segmentation without the need for data augmentation and complex post-processing refinement. In the second step, we formulate the landmark localization problem directly on the geodesic space for sparsely-spaced anatomical landmarks. In the third step, we utilize a long short-term memory network to identify the closely-spaced landmarks, which is rather difficult to obtain using other standard networks. The proposed fully automated method showed superior efficacy compared to the state-of-the-art mandible segmentation and landmarking approaches in craniofacial anomalies and diseased states. We used a very challenging CBCT data set of 50 patients with a high-degree of craniomaxillofacial variability that is realistic in clinical practice. The qualitative visual inspection was conducted for distinct CBCT scans from 250 patients with high anatomical variability. We have also shown the state-of-the-art performance in an independent data set from the MICCAI Head-Neck Challenge (2015).

Data-driven method to enhance craniofacial and oral phenotype vocabularies.

BACKGROUND: A significant amount of clinical information captured as free-text narratives could be better used for several applications, such as clinical decision support, ontology development, evidence-based practice, and research. The Human Phenotype Ontology (HPO) is specifically used for semantic comparisons for diagnostic purposes. All these functions require quality coverage of the domain of interest. The authors used natural language processing to capture craniofacial and oral phenotype signatures from electronic health records and then used these signatures for evaluation of existing oral phenotype ontology coverage. METHODS: The authors applied a text-processing pipeline based on the clinical Text Analysis and Knowledge Extraction System to annotate the clinical notes with Unified Medical Language System codes. The authors extracted the disease or disorder phenotype terms, which were then compared with HPO terms and their synonyms. RESULTS: The authors retrieved 2,153 deidentified clinical notes from 558 patients. Finally, 2,416 unique diseases or disorders phenotype terms were extracted, which included 210 craniofacial or oral phenotype terms. Twenty-six of these phenotypes were not found in the HPO. CONCLUSIONS: The authors demonstrated that natural language processing tools could extract relevant phenotype terms from clinical narratives, which could help identify gaps in existing ontologies and enhance craniofacial and dental phenotyping vocabularies. PRACTICAL IMPLICATIONS: The expansion of terms in the dental, oral, and craniofacial domains in the HPO is particularly important as the dental community moves toward electronic health records.

Determinants of outcomes after resection of renal cell carcinoma with venous involvement.

PURPOSE: To determine the outcomes and to identify prognostic variables determining mortality and recurrence after surgery for renal cell cancer (RCC) with venous involvement. METHODS: Retrospective evaluation of the medical records of 132 patients with RCC and tumor thrombi treated at Johns Hopkins Hospital (1997-2008) was done. Kaplan-Meier analysis was used to determine survivals. Uni- and multivariate Cox proportional analysis was done to identify predictors for recurrence, all-cause mortality (ACM) and cancer-specific mortality (CSM). RESULTS: Mean follow-up was 30.3 (0.03-159.5) months. Sixty-four (48.5%) patients had renal vein thrombus (Group 1), 55 (41.7%) had subdiaphragmatic inferior vena cava (IVC) tumor thrombus (Group 2), while 13 (9.8%) had involvement of IVC above diaphragm or atrial extension (Group 3). IVC thrombus was more common from the right-sided tumors. Patients with higher thrombus levels had more blood loss and complicated and longer hospital stay. Thrombus level was not found to be a predictor of recurrence, ACM and CSM. One- and three-year recurrence-free survivals for non-metastatic patients were 69 and 53%. Tumor size (p=0.015), grade (p=0.007) and venous wall invasion (p=0.027) were predictors for recurrence. Five-year overall survival was 48, 35 and 13% for 3 groups, respectively. Presence of distant metastasis (p=0.032), size (p=0.002), histology (p=0.020) and grade (p=0.013) were predictors of ACM. Five-year cancer-specific survival was 65, 43 and 36 for 3 groups, respectively. Tumor size (p=0.001) and distant metastasis at presentation (p=0.025) were the predictors of CSM. CONCLUSIONS: Tumor thrombus level does not predict recurrence or mortality in RCC with venous involvement. Survival is determined by inherent aggressiveness of the cancer manifested by tumor size, grade and distant metastasis at presentation.

Single-center comparative oncologic outcomes of surgical and percutaneous cryoablation for treatment of renal tumors.

PURPOSE: To compare outcomes between patients undergoing surgical and percutaneous cryoablation for treatment of renal masses and identify prognostic variables that determine survival. PATIENTS AND METHODS: We retrospectively evaluated the medical records of 194 patients who underwent cryoablation for renal tumors between 1997 and 2008 at a single large center. Patient demographics, tumor characteristics, perioperative data, and follow-up details were recorded. Univariate and multivariate Cox proportional hazards analysis was performed to identify predictors of overall (OS), cancer-specific (CSS), and recurrence-free survival (RFS). RESULTS: Cryoablation was performed percutaneously (PCA) in 141 patients for 154 tumors, while 53 patients were treated surgically (SCA) using an open or laparoscopic approach for 54 tumors. Mean follow-up was 44.5 months in SCA and 36.1 months in PCA. PCA had a shorter duration of hospital stay (0.7 days vs 3.2 days, P<0.0001). The rate of residual (P=0.38) and recurrent disease (P=0.18) was not significantly different between the two groups. Five-year OS, CSS, and RFS were 78.81%, 100%, and 85.23% for SCA, and 77.71%, 98%, and 95.56% for PCA, respectively; the type of approach was not predictive of OS, CSS, and RFS. CONCLUSIONS: SCA and PCA both provide adequate oncologic control for renal masses. Duration of hospital stay was lower in patients undergoing PCA.