Integrative bioinformatics approach for identifying key genes and potential therapeutic targets in the concurrent manifestation of hypertrophic cardiomyopathy and pulmonary hypertension.

Background: Hypertrophic cardiomyopathy (HCM), identified as a primary cause of sudden cardiac death (SCD), intertwines with pulmonary hypertension (PH) to amplify cardiovascular morbidity. This complex synergy poses significant therapeutic challenges due to the absence of drugs specifically targeting their concurrent manifestation. This study seeks to unravel the molecular intricacies linking HCM and PH, aiming to lay the groundwork for targeted therapeutic interventions. Methods: Through the analysis of gene expression profiles from datasets GSE36961 (HCM) and GSE113439 (PH) within the public data repository of Gene Expression Omnibus (GEO), this research systematically identified differentially expressed genes (DEGs), conducted extensive functional annotations, and constructed detailed protein-protein interaction (PPI) networks to uncover crucial hub genes. Further, co-expression analyses, alongside drug prediction and molecular docking simulations, were employed to pinpoint potential therapeutic agents that could ameliorate the combined pathology of HCM and PH. Results: Our comprehensive analysis unearthed 79 DEGs shared between HCM and PH, highlighting fourteen as pivotal hub genes. Validation across three additional datasets (GSE35229, GSE32453, and GSE53408) from GEO accentuated secreted phosphoprotein 1 (SPP1) as a key gene of interest. Remarkably, the study identified tacrolimus, ponatinib, bosutinib, dasatinib, doxorubicin, and zanubrutinib as promising drugs for addressing the dual challenge of HCM and PH. Conclusions: The findings of this investigation shed light on the genetic underpinnings of HCM and PH's simultaneous occurrence, emphasizing the central role of SPP1 in their pathogenesis. The identification of six candidate drugs offers a hopeful vista for future therapeutic strategies targeting this complex cardiovascular interplay, marking a significant stride towards mitigating the compounded morbidity of HCM and PH. Future mechanistic and clinical studies are warranted for the investigation of this potential target and therapeutics.

Association between Periodontitis and Mild Cognitive Impairment: A Systematic Review and Meta-Analysis.

INTRODUCTION: The connection between periodontitis and mild cognitive impairment (MCI) continues to receive attention. However, whether periodontitis is a risk factor for MCI remains still uncertain. This study aims to systematically analyze the available literature regarding the relationship between periodontitis and the risk of developing MCI and whether the periodontal health of MCI patients is poorer. METHODS: A literature search of PubMed, Scopus, Embase, and Web of Science databases was conducted to include all studies on the relationship between periodontitis and MCI from inception to April 2023. The studies were independently screened by 2 researchers, and those meeting the inclusion criteria were extracted and cross-checked. Pooled odds ratio (OR) or mean difference (MD) with 95% confidence intervals (CI) was calculated using either a fixed-effects or random-effects model. RESULTS: Seven studies with a total of 3,973 participants were included. Meta-analysis results showed a statistically significant higher incidence of MCI in patients with periodontitis (OR, 1.70 (95% CI: 1.24-2.32, p < 0.001) compared to healthy participants. A subgroup meta-analysis showed that the pooled OR for the risk of MCI in patients with severe periodontitis was 2.09 (95% CI: 1.49-2.92, p < 0.001). In addition, attachment loss (MD = 0.44, 95% CI: 0.12-0.75, p < 0.001) and plaque index (MD = 0.72, 95% CI: 0.50-0.93, p < 0.001) were higher in MCI patients compared with the control group, but the pocket probing depth (MD = 0.21, 95% CI: -0.08 to 0.49, p = 0.15) was not significantly different between the two groups. CONCLUSIONS: Patients with periodontitis are at a higher risk of developing MCI, and the periodontal health of MCI patients is generally compromised. However, further well-designed studies should be conducted to confirm this relationship between MCI and periodontitis.

Apoptotic bodies: bioactive treasure left behind by the dying cells with robust diagnostic and therapeutic application potentials.

Apoptosis, a form of programmed cell death, is essential for growth and tissue homeostasis. Apoptotic bodies (ApoBDs) are a form of extracellular vesicles (EVs) released by dying cells in the last stage of apoptosis and were previously regarded as debris of dead cells. Recent studies unraveled that ApoBDs are not cell debris but the bioactive treasure left behind by the dying cells with an important role in intercellular communications related to human health and various diseases. Defective clearance of ApoBDs and infected-cells-derived ApoBDs are possible etiology of some diseases. Therefore, it is necessary to explore the function and mechanism of the action of ApoBDs in different physiological and pathological conditions. Recent advances in ApoBDs have elucidated the immunomodulatory, virus removal, vascular protection, tissue regenerative, and disease diagnostic potential of ApoBDs. Moreover, ApoBDs can be used as drug carriers enhancing drug stability, cellular uptake, and targeted therapy efficacy. These reports from the literature indicate that ApoBDs hold promising potential for diagnosis, prognosis, and treatment of various diseases, including cancer, systemic inflammatory diseases, cardiovascular diseases, and tissue regeneration. This review summarizes the recent advances in ApoBDs-related research and discusses the role of ApoBDs in health and diseases as well as the challenges and prospects of ApoBDs-based diagnostic and therapeutic applications.

Cannabidiol Rescues TNF-α-Inhibited Proliferation, Migration, and Osteogenic/Odontogenic Differentiation of Dental Pulp Stem Cells.

Strategies to promote dental pulp stem cells (DPSCs) functions including proliferation, migration, pro-angiogenic effects, and odontogenic/osteogenic differentiation are in urgent need to restore pulpitis-damaged dentin/pulp regeneration and DPSCs-based bone tissue engineering applications. Cannabidiol (CBD), an active component of Cannabis sativa has shown anti-inflammation, chemotactic, anti-microbial, and tissue regenerative potentials. Based on these facts, this study aimed to analyze the effect of CBD on DPSCs proliferation, migration, and osteogenic/odontogenic differentiation in basal and inflammatory conditions. Highly pure DPSCs with characteristics of mesenchymal stem cells (MSCs) were successfully isolated, as indicated by the results of flowcytometry and multi-lineage (osteogenic, adipogenic, and chondrogenic) differentiation potentials. Among the concentration tested (0.1-12.5 µM), CBD (2.5 µM) showed the highest anabolic effect on the proliferation and osteogenic/odontogenic differentiation of DPSCs. Pro-angiogenic growth factor VEGF mRNA expression was robustly higher in CBD-treated DPSCs. CBD also prompted the migration of DPSCs and CBD receptor CB1 and CB2 expression in DPSCs. TNF-α inhibited the viability, migration, and osteogenic/odontogenic differentiation of DPSCs and CBD reversed these effects. CBD alleviated the TNF-α-upregulated expression of pro-inflammatory cytokines TNF-α, interleukin (IL)-1ß, and IL-6 in DPSCs. In conclusion, our results indicate the possible application of CBD on DPSCs-based dentin/pulp and bone regeneration.

An automated treatment plan alert system to safeguard cancer treatments in radiation therapy.

In radiation oncology, the intricate process of delivering radiation to a patient is detailed by the patient's treatment plan, which is data describing the geometry, construction and strength of the radiation machine and the radiation beam it emits. The patient's life depends upon the accuracy of the treatment plan, which is left in the hands of the vendor-specific software automatically generating the plan after an initial patient consultation and planning with a medical professional. However, corrupted and erroneous treatment plan data have previously resulted in severe patient harm when errors go undetected and radiation proceeds. The aim of this paper is to develop an automatic error-checking system to prevent the accidental delivery of radiation treatment to an area of the human body (i.e., the treatment site) that differs from the plan's documented intended site. To this end, we develop a method for structuring treatment plan data in order to feed machine-learning (ML) classifiers and predict a plan's treatment site. In practice, a warning may be raised if the prediction disagrees with the documented intended site. The contribution of this paper is in the strategic structuring of the complex, intricate, and nonuniform data of modern treatment planning and from multiple vendors in order to easily train ML algorithms. A three-step process utilizing up- and down-sampling and dimension reduction, the method we develop in this paper reduces the thousands of parameters comprising a single treatment plan to a single two-dimensional heat map that is independent of the specific vendor or construction of the machine used for treatment. Our heat-map structure lends itself well to feed well-established ML algorithms, and we train-test random forest, softmax, k-nearest neighbors, shallow neural network, and support vector machine using real clinical treatment plans from several hospitals in the United States. The paper demonstrates that the proposed method characterizes treatment sites so well that ML classifiers may predict head-neck, breast, and prostate treatment sites with an accuracy of about 94%. The proposed method is the first step towards a thorough, fully automated error-checking system in radiation therapy.

Designing of Highly Efficient Oxygen Evolution Reaction Electrocatalysts Utilizing A Correlation Factor: Theory and Experiment.

The theoretical prediction of the catalytic activity is very beneficial for the design of highly efficient catalysts. At present, most theoretical descriptors focus on estimating the catalytic activity and understanding the enhancement mechanism of catalysts, while it is also quite important to find a factor to correlate the descriptors with preparation methods. In this work, a correlation factor, the d electron density of transition metal ions, was developed to correlate the d band center values of transition metal ions with the preparation methods of amorphization and Al introduction. According to the results of theoretical simulations, the correlation factor not only exhibited favorable linear relationships with the theoretical overpotentials of (CoFeAlx)3O4 and (CoFeAlx)3O4 + (CoFeAlx)OOH systems but also correlated with two preparation methods by altering the volume of systems. Based on theoretical guidance, the electrocatalytic activities of the prepared (CoFeAlx)3O4 specimens were gradually improved by the preparation methods of amorphization and Al introduction, and the Am-CoFeAl-2-10h specimen exhibited a low kinetic barrier of 268 mV, fast charge transfer rate, and stable electrocatalytic activity. This strategy could be applied to design highly efficient catalysts by adjusting the correlation factor of the active site with suitable preparation methods.

A fully automated on-line salting-out assisted liquid-liquid extraction capillary electrophoresis methodology: Application to tyrosine kinase inhibitors in human plasma.

A fully automated analytical methodology combining salting-out assisted liquid-liquid extraction (SALLE) and capillary electrophoresis (CE) for the analysis of three Tyrosine Kinase Inhibitors (TKIs) in plasma samples is proposed. The automated methodology, called A-SALLE-CE-UV, makes full use of the advantages of both techniques by combining desalting, protein precipitation, automated liquid-liquid extraction, in-line CE stacking and electrophoretic separation of analytes in plasma samples in a fully integrated way. At first, the capillary is used to deliver appropriate micro-volumes of extraction agent solutions (acetonitrile, salt) in the plasma sample. ACN and salting-out agent (NaCl) solutions are added by pressure from outlet vials into the sample vial (inlet) containing human plasma sample spiked with the three tested TKIs. After addition of both ACN and NaCl solutions, mixing is achieved by generating air bubbles leading to a two phases separation and extraction of TKIs in the upper mostly organic phase (ACN). The upper phase containing the TKIs is then injected and analysed by CE-UV. Due to the presence of ACN, the analytes are stacked in-line and successfully separated in the same capillary. The results obtained in terms of limit of detection (LOD), limit of quantification (LOQ), sensitivity enhancement factor (SEF), repeatability and linearity demonstrate the applicability of the proposed method for possible therapeutic drug monitoring (TDM) of TKIs.

The Dosimetric and Temporal Effects of Respiratory-Gated, High-Dose-Rate Radiation Therapy in Patients With Lung Cancer.

PURPOSE: To evaluate the dosimetric and temporal effects of high-dose-rate respiratory-gated radiation therapy in patients with lung cancer. METHODS: Treatment plans from 5 patients with lung cancer (3 nongated and 2 gated at 80EX-80IN) were retrospectively evaluated. Prescription dose for these patients varied from 8 to 18 Gy/fraction with 3 to 5 treatment fractions. Using the same treatment planning criteria, 4 new treatment plans, corresponding to 4 gating windows (20EX-20IN, 40EX-40IN, 60EX-60IN, and 80EX-80IN), were generated for each patient. Mean tumor dose, mean lung dose, and lung V20 were used to assess the dosimetric effects. A MATLAB algorithm was developed to compute treatment time. RESULTS: Mean lung dose and lung V20 were on average reduced between -16.1% to -6.0% and -20.0% to -7.2%, respectively, for gated plans when compared to the corresponding nongated plans, and between -5.8% to -4.2% and -7.0% to -5.4%, respectively, for plans with smaller gating windows when compared to the corresponding plans gated at 80EX-80IN. Treatment delivery times of gated plans using high-dose rate were reduced on average between -19.7% (-0.10 min/100 MU) and -27.2% (-0.13 min/100 MU) for original nongated plans and -15.6% (-0.15 min/100 MU) and -20.3% (-0.19 min/100 MU) for original 80EX-80IN-gated plans. CONCLUSION: Respiratory-gated radiation therapy in patients with lung cancer can reduce lung dose while maintaining tumor dose. Because treatment delivery during gated therapy is discontinuous, total treatment time may be prolonged. However, this increase in treatment time can be offset by increasing the dose delivery rate. Estimation of treatment time may be helpful in selecting patients for respiratory gating and choosing appropriate gating windows.

Impact of temporal probability in 4D dose calculation for lung tumors.

The purpose of this study was to evaluate the dosimetric uncertainty in 4D dose calculation using three temporal probability distributions: uniform distribution, sinusoidal distribution, and patient-specific distribution derived from the patient respiratory trace. Temporal probability, defined as the fraction of time a patient spends in each respiratory amplitude, was evaluated in nine lung cancer patients. Four-dimensional computed tomography (4D CT), along with deformable image registration, was used to compute 4D dose incorporating the patient's respiratory motion. First, the dose of each of 10 phase CTs was computed using the same planning parameters as those used in 3D treatment planning based on the breath-hold CT. Next, deformable image registration was used to deform the dose of each phase CT to the breath-hold CT using the deformation map between the phase CT and the breath-hold CT. Finally, the 4D dose was computed by summing the deformed phase doses using their corresponding temporal probabilities. In this study, 4D dose calculated from the patient-specific temporal probability distribution was used as the ground truth. The dosimetric evaluation matrix included: 1) 3D gamma analysis, 2) mean tumor dose (MTD), 3) mean lung dose (MLD), and 4) lung V20. For seven out of nine patients, both uniform and sinusoidal temporal probability dose distributions were found to have an average gamma passing rate > 95% for both the lung and PTV regions. Compared with 4D dose calculated using the patient respiratory trace, doses using uniform and sinusoidal distribution showed a percentage difference on average of -0.1% ± 0.6% and -0.2% ± 0.4% in MTD, -0.2% ± 1.9% and -0.2% ± 1.3% in MLD, 0.09% ± 2.8% and -0.07% ± 1.8% in lung V20, -0.1% ± 2.0% and 0.08% ± 1.34% in lung V10, 0.47% ± 1.8% and 0.19% ± 1.3% in lung V5, respectively. We concluded that four-dimensional dose computed using either a uniform or sinusoidal temporal probability distribution can approximate four-dimensional dose computed using the patient-specific respiratory trace.

A real-time applicator position monitoring system for gynecologic intracavitary brachytherapy.

PURPOSE: To develop a real-time applicator position monitoring system (RAPS) for intracavitary brachytherapy using an infrared camera and reflective markers. METHODS: 3D image-guided brachytherapy requires high accuracy of applicator localization; however, applicator displacement can happen during patient transfer for imaging and treatment delivery. No continuous applicator position monitoring system is currently available. The RAPS system was developed for real-time applicator position monitoring without additional radiation dose to patients. It includes an infrared camera, reflective markers, an infrared illuminator, and image processing software. After reflective markers are firmly attached to the applicator and the patient body, applicator displacement can be measured by computing the relative change in distance between the markers. The reflective markers are magnetic resonance imaging (MRI) compatible, which is suitable for MRI-guided HDR brachytherapy paradigm. In our prototype, a Microsoft Kinect sensor with a resolution of 640 by 480 pixels is used as an infrared camera. A phantom study was carried out to compare RAPS' measurements with known displacements ranging from -15 to +15 mm. A reproducibility test was also conducted. RESULTS: The RAPS can achieve 4 frames/s using a laptop with Intel(®) Core™2 Duo processor. When the pixel size is 0.95 mm, the difference between RAPS' measurements and known shift values varied from 0 to 0.8 mm with the mean value of 0.1 mm and a standard deviation of 0.44 mm. The system reproducibility was within 0.6 mm after ten reposition trials. CONCLUSIONS: This work demonstrates the feasibility of a real-time infrared camera based gynecologic intracavitary brachytherapy applicator monitoring system. Less than 1 mm accuracy is achieved when using an off-the-shelf infrared camera.

A computer aided treatment event recognition system in radiation therapy.

PURPOSE: To develop an automated system to safeguard radiation therapy treatments by analyzing electronic treatment records and reporting treatment events. METHODS: CATERS (Computer Aided Treatment Event Recognition System) was developed to detect treatment events by retrieving and analyzing electronic treatment records. CATERS is designed to make the treatment monitoring process more efficient by automating the search of the electronic record for possible deviations from physician's intention, such as logical inconsistencies as well as aberrant treatment parameters (e.g., beam energy, dose, table position, prescription change, treatment overrides, etc). Over a 5 month period (July 2012-November 2012), physicists were assisted by the CATERS software in conducting normal weekly chart checks with the aims of (a) determining the relative frequency of particular events in the authors' clinic and (b) incorporating these checks into the CATERS. During this study period, 491 patients were treated at the University of Iowa Hospitals and Clinics for a total of 7692 fractions. RESULTS: All treatment records from the 5 month analysis period were evaluated using all the checks incorporated into CATERS after the training period. About 553 events were detected as being exceptions, although none of them had significant dosimetric impact on patient treatments. These events included every known event type that was discovered during the trial period. A frequency analysis of the events showed that the top three types of detected events were couch position override (3.2%), extra cone beam imaging (1.85%), and significant couch position deviation (1.31%). The significant couch deviation is defined as the number of treatments where couch vertical exceeded two times standard deviation of all couch verticals, or couch lateral/longitudinal exceeded three times standard deviation of all couch laterals and longitudinals. On average, the application takes about 1 s per patient when executed on either a desktop computer or a mobile device. CONCLUSIONS: CATERS offers an effective tool to detect and report treatment events. Automation and rapid processing enables electronic record interrogation daily, alerting the medical physicist of deviations potentially days prior to performing weekly check. The output of CATERS could also be utilized as an important input to failure mode and effects analysis.

High resolution (3 Tesla) MRI-guided conformal brachytherapy for cervical cancer: consequences of different high-risk CTV sizes.

PURPOSE: To evaluate conventional brachytherapy (BT) plans using dose-volume parameters and high resolution (3 Tesla) MRI datasets, and to quantify dosimetric benefits and limitations when MRI-guided, conformal BT (MRIG-CBT) plans are generated. MATERIAL AND METHODS: Fifty-five clinical high-dose-rate BT plans from 14 cervical cancer patients were retrospectively studied. All conventional plans were created using MRI with titanium tandem-and-ovoid applicator (T&O) for delivery. For each conventional plan, a MRIG-CBT plan was retrospectively generated using hybrid inverse optimization. Three categories of high risk (HR)-CTV were considered based on volume: non-bulky (< 20 cc), low-bulky (> 20 cc and < 40 cc) and bulky (≥ 40 cc). Dose-volume metrics of D90 of HR-CTV and D2cc and D0.1cc of rectum, bladder, and sigmoid colon were analyzed. RESULTS: Tumor coverage (HR-CTV D90) of the conventional plans was considerably affected by the HR-CTV size. Sixteen percent of the plans covered HR-CTV D90 with the prescription dose within 5%. At least one OAR had D2cc values over the GEC-ESTRO recommended limits in 52.7% of the conventional plans. MRIG-CBT plans showed improved target coverage for HR-CTV D90 of 98 and 97% of the prescribed dose for non-bulky and low-bulky tumors, respectively. No MRIG-CBT plans surpassed the D2cc limits of any OAR. Only small improvements (D90 of 80%) were found for large targets (> 40 cc) when using T&O applicator approach. CONCLUSIONS: MRIG-CBT plans displayed considerable improvement for tumor coverage and OAR sparing over conventional treatment. When the HR-CTV volume exceeded 40 cc, its improvements were diminished when using a conventional intracavitary applicator.

A real-time respiratory motion monitoring system using KINECT: proof of concept.

PURPOSE: The purpose of this study is to investigate the feasibility of a low-cost respiratory motion monitoring system based on the Microsoft KINECT sensor. METHODS: The authors increased KINECT's inherent depth resolution from 1 cm to 1 mm via a motion magnification system. Using the KINECT software development kit, the authors programmed the KINECT to capture depth images and determine the average depth over a thoracic region of interest, viewed almost parallel to the subject's surface. KINECT respiratory traces (average depth vs time at a rate of 30 Hz) were acquired from four volunteers and compared with those simultaneously acquired using a commercially available strain gauge respiratory gating system. RESULTS: The correlation coefficient (CC) between KINECT and strain gauge traces varied from 0.958 to 0.978, with a mean CC of 0.969. This strong correlation was also demonstrated by the joint probability distribution and visual inspection. CONCLUSIONS: It is feasible to use the KINECT for respiratory motion tracking. Traces are similar to those of a clinically used strain gauge system. The KINECT-based system provides a new and economical way to monitor respiratory motion.

High performance computing for deformable image registration: towards a new paradigm in adaptive radiotherapy.

The advent of readily available temporal imaging or time series volumetric (4D) imaging has become an indispensable component of treatment planning and adaptive radiotherapy (ART) at many radiotherapy centers. Deformable image registration (DIR) is also used in other areas of medical imaging, including motion corrected image reconstruction. Due to long computation time, clinical applications of DIR in radiation therapy and elsewhere have been limited and consequently relegated to offline analysis. With the recent advances in hardware and software, graphics processing unit (GPU) based computing is an emerging technology for general purpose computation, including DIR, and is suitable for highly parallelized computing. However, traditional general purpose computation on the GPU is limited because the constraints of the available programming platforms. As well, compared to CPU programming, the GPU currently has reduced dedicated processor memory, which can limit the useful working data set for parallelized processing. We present an implementation of the demons algorithm using the NVIDIA 8800 GTX GPU and the new CUDA programming language. The GPU performance will be compared with single threading and multithreading CPU implementations on an Intel dual core 2.4 GHz CPU using the C programming language. CUDA provides a C-like language programming interface, and allows for direct access to the highly parallel compute units in the GPU. Comparisons for volumetric clinical lung images acquired using 4DCT were carried out. Computation time for 100 iterations in the range of 1.8-13.5 s was observed for the GPU with image size ranging from 2.0 x 10(6) to 14.2 x 10(6) pixels. The GPU registration was 55-61 times faster than the CPU for the single threading implementation, and 34-39 times faster for the multithreading implementation. For CPU based computing, the computational time generally has a linear dependence on image size for medical imaging data. Computational efficiency is characterized in terms of time per megapixels per iteration (TPMI) with units of seconds per megapixels per iteration (or spmi). For the demons algorithm, our CPU implementation yielded largely invariant values of TPMI. The mean TPMIs were 0.527 spmi and 0.335 spmi for the single threading and multithreading cases, respectively, with <2% variation over the considered image data range. For GPU computing, we achieved TPMI =0.00916 spmi with 3.7% variation, indicating optimized memory handling under CUDA. The paradigm of GPU based real-time DIR opens up a host of clinical applications for medical imaging.