BACKGROUND: Acute exacerbations of chronic obstructive pulmonary disease (AECOPD) are associated with high mortality, morbidity, and poor quality of life and constitute a substantial burden to patients and health care systems. New approaches to prevent or reduce the severity of AECOPD are urgently needed. Internationally, this has prompted increased interest in the potential of remote patient monitoring (RPM) and digital medicine. RPM refers to the direct transmission of patient-reported outcomes, physiological, and functional data, including heart rate, weight, blood pressure, oxygen saturation, physical activity, and lung function (spirometry), directly to health care professionals through automation, web-based data entry, or phone-based data entry. Machine learning has the potential to enhance RPM in chronic obstructive pulmonary disease by increasing the accuracy and precision of AECOPD prediction systems.
OBJECTIVE: This study aimed to conduct a dual systematic review. The first review focuses on randomized controlled trials where RPM was used as an intervention to treat or improve AECOPD. The second review examines studies that combined machine learning with RPM to predict AECOPD. We review the evidence and concepts behind RPM and machine learning and discuss the strengths, limitations, and clinical use of available systems. We have generated a list of recommendations needed to deliver patient and health care system benefits.
METHODS: A comprehensive search strategy, encompassing the Scopus and Web of Science databases, was used to identify relevant studies. A total of 2 independent reviewers (HMGG and CM) conducted study selection, data extraction, and quality assessment, with discrepancies resolved through consensus. Data synthesis involved evidence assessment using a Critical Appraisal Skills Programme checklist and a narrative synthesis. Reporting followed PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines.
RESULTS: These narrative syntheses suggest that 57% (16/28) of the randomized controlled trials for RPM interventions fail to achieve the required level of evidence for better outcomes in AECOPD. However, the integration of machine learning into RPM demonstrates promise for increasing the predictive accuracy of AECOPD and, therefore, early intervention.
CONCLUSIONS: This review suggests a transition toward the integration of machine learning into RPM for predicting AECOPD. We discuss particular RPM indices that have the potential to improve AECOPD prediction and highlight research gaps concerning patient factors and the maintained adoption of RPM. Furthermore, we emphasize the importance of a more comprehensive examination of patient and health care burdens associated with RPM, along with the development of practical solutions.

Railway Point Machine (RPM) is a fundamental component of railway infrastructure and plays a crucial role in ensuring the safe operation of trains. Its primary function is to divert trains from one track to another, enabling connections between different lines and facilitating route selection. By judiciously deploying turnouts, railway systems can provide efficient transportation services while ensuring the safety of passengers and cargo. As signal processing technologies develop rapidly, taking the easy acquisition advantages of audio signals, a fault diagnosis method for RPMs is proposed by considering noise and multi-channel signals. The proposed method consists of several stages. Initially, the signal is subjected to pre-processing steps, including cropping and channel separation. Subsequently, the signal undergoes noise addition using the Random Length and Dynamic Position Noises Superposition (RDS) module, followed by conversion to a greyscale image. To enhance the data, Synthetic Minority Oversampling Technique (SMOTE) module is applied. Finally, the training data is fed into a Dual-input Attention Convolutional Neural Network (DIACNN). By employing various experimental techniques and designing diverse datasets, our proposed method demonstrates excellent robustness and achieves an outstanding classification accuracy of 99.73%.

The olfactory epithelium undergoes neuronal regeneration from basal stem cells and is susceptible to olfactory neuroblastoma (ONB), a rare tumor of unclear origins. Employing alterations in Rb1/Trp53/Myc (RPM), we establish a genetically engineered mouse model of high-grade metastatic ONB exhibiting a NEUROD1+ immature neuronal phenotype. We demonstrate that globose basal cells (GBCs) are a permissive cell of origin for ONB and that ONBs exhibit cell fate heterogeneity that mimics normal GBC developmental trajectories. ASCL1 loss in RPM ONB leads to emergence of non-neuronal histopathologies, including a POU2F3+ microvillar-like state. Similar to small-cell lung cancer (SCLC), mouse and human ONBs exhibit mutually exclusive NEUROD1 and POU2F3-like states, an immune-cold tumor microenvironment, intratumoral cell fate heterogeneity comprising neuronal and non-neuronal lineages, and cell fate plasticity-evidenced by barcode-based lineage tracing and single-cell transcriptomics. Collectively, our findings highlight conserved similarities between ONB and neuroendocrine tumors with significant implications for ONB classification and treatment.

OBJECTIVE: Today, respiratory movement can be monitored and recorded with different methods during a simulation on a four-dimensional (4D) computed tomography (CT) device to be used in radiotherapy planning. A synchronized respiratory monitoring system (RPM) with an externally equipped device is one of these methods. Another method is to create 4D images of the patient\'s breathing phases without the need for extra equipment, with an anatomy-based software program integrated into the CT device. Our aim is to compare the RPM system and the software system (Deviceless) which are two different respiratory monitoring methods used in tracking moving targets during 4D-CT imaging and to assess their clinical usability.
METHODS: Ten patients who underwent paraaortic nodal irradiation were enrolled. The simulation was performed using intravenous contrast material on a 4D-CT device with both respiratory monitoring methods. The right/left kidneys and renal arteries were chosen as references to evaluate abdominal organ movement. It was then manually contoured one by one on both sets of images. The images were compared volumetrically and geometrically after rigid reconstruction. The similarity between the contours was determined by the Dice index. Wilcoxon test was used for statistical comparisons.
RESULTS: The motion of the kidneys in all three directions was found to be 0.0 cm in both methods. The shifts in the right/left renal arteries were submillimetric. The Dice index showed a high similarity in both kidney and renal artery contours.
CONCLUSIONS: In our study, no difference was found between RPM and Deviceless systems used for tracking and detection of moving targets during simulation in 4D-CT. Both methods can be used safely for radiotherapy planning according to the available possibilities in the clinic.

The aim of this study was to evaluate the effect of rotation frequency (rpm) of different polishing discs on the surface roughness of a nanohybrid resin composite material. 126 specimens were prepared in metal molds of 10 mm diameter and 2 mm depth using a nanohybrid resin composite material. The prepared specimens were kept in distilled water for 24 hours. Polishing treatments at 5k, 10k, 15k, and 20k rpm were applied to the nanohybrid resin composite material by grouping different brand polishing discs: Sof-Lex Contouring and Polishing Discs (3M Espe, USA) (3M Group), Optidisc (Kerr Corporation, USA) (Kerr Group), Super-Snap Rainbow Technique Kit (Shofu Dental, Japan) (Shofu Group), Finishing Disc (Bisco Dental, USA) (Bisco Group). The surface roughness was evaluated at three different points by atomic force microscopy for all specimens and scanning electron microscopy was used for visual assessment. Data were evaluated by Two Way ANOVA and Tukey\'s HSD Test. The mean surface roughness (Ra, μm) of all prepared samples showed significant differences (α = 0.05). According to Two-Way ANOVA, there is a statistically significant relationship between the rpm values and the discs. The 3M group showed the highest roughness value at all rpm speeds. Shofu group at 15k, 20k rpm, Bisco group at 10k, 15k, 20k rpm, the Kerr group at 15k, 20k rpm showed the lowest roughness value and had roughness close to the surfaces finished with a mylar strip. The smoothest surfaces were obtained at 15k rpm, even though polishing discs from different brands were used. It was also observed that 5k and 20k rpm polishing speeds can increase the surface roughness of the nanohybrid resin composite material.

Background: Remote patient monitoring (RPM) has potential in hypertension management, but limited studies have focused on maternal hypertension, especially among vulnerable populations. The objective of this study was to integrate RPM into perinatal care for pregnant patients at elevated risk of hypertensive disorders to show feasibility, acceptability, and safety. Methods: A prospective pilot cohort study was conducted at the University of Mississippi Medical Center 2021-2023. Participants\' blood pressure readings were remotely captured and monitored until 8-week postpartum, with timely assessment and intervention. Results: Out of 98 enrollees, 77 utilized RPM, and no maternal or neonatal deaths occurred within 60-day postpartum. High program satisfaction was reported at discharge. Conclusion: This study demonstrates the feasibility and acceptability of RPM for perinatal care in a vulnerable population. Positive outcomes were observed, including high patient satisfaction and no maternal or neonatal deaths. Further research should address patient engagement barriers and develop tailored protocols for improved clinical outcomes.

OBJECTIVE: Beam delivery latency in respiratory-gated particle therapy systems is a crucial issue to dose delivery accuracy. The aim of this study is to develop a multi-channel signal acquisition platform for investigating gating latencies occurring within RPM respiratory gating system (Varian, USA) and ProBeam proton treatment system (Varian, USA) individually.
METHODS: The multi-channel signal acquisition platform consisted of several electronic components, including a string position sensor for target motion detection, a photodiode for proton beam sensing, an interfacing board for accessing the trigger signal between the respiratory gating system and the proton treatment system, a signal acquisition device for sampling and synchronizing signals from the aforementioned components, and a laptop for controlling the signal acquisition device and data storage. RPM system latencies were determined by comparing the expected gating phases extracted from the motion signal with the trigger signal\'s state turning points. ProBeam system latencies were assessed by comparing the state turning points of the trigger signal with the beam signal. The total beam delivery latencies were calculated as the sum of delays in the respiratory gating system and the cyclotron proton treatment system. During latency measurements, simulated sinusoidal motion were applied at different amplitudes and periods for complete beam delivery latency evaluation under different breathing patterns. Each breathing pattern was repeated 30 times for statistical analysis.
RESULTS: The measured gating ON/OFF latencies in the RPM system were found to be 104.20 ± 13.64 ms and 113.60 ± 14.98 ms, respectively. The measured gating ON/OFF delays in the ProBeam system were 108.29 ± 0.85 ms and 1.20 ± 0.04 ms, respectively. The total beam ON/OFF latencies were determined to be 212.50 ± 13.64 ms and 114.80 ± 14.98 ms.
CONCLUSIONS: With the developed multi-channel signal acquisition platform, it was able to investigate the gating lags happened in both the respiratory gating system and the proton treatment system. The resolution of the platform is enough to distinguish the delays at the millisecond time level. Both the respiratory gating system and the proton treatment system made contributions to gating latency. Both systems contributed nearly equally to the total beam ON latency, with approximately 100 ms. In contrast, the respiratory gating system was the dominant contributor to the total beam OFF latency.

UNASSIGNED: The aim of the study was to investigate patient satisfaction, saving of time and the possible reduction of visits to medical practices that use Remote Patient Monitoring (RPM) during treatment compared to usual care.
UNASSIGNED: In a randomized controlled trial between October 2020 and May 2021, the participating medical practices were randomized into three groups (two different RPM systems, one control). Doctors were required to enroll patients ≥18 years with acute respiratory infection in possession of a web-enabled device, such as a laptop, tablet or computer. After a three-month study phase, doctors were asked to describe the treatment of their patients via online survey. Patients were also questioned. The analysis was carried out descriptively and through group comparisons.
UNASSIGNED: 51 practices with 121 patients were included. Overall, the results generally show a positive assessment of digital care on the patient side. As for the doctors, handling and integrating the systems into established practice routines seem to be a challenge. Further, the number of patient visits to the medical practice was not reduced by using the systems. Doctors did not save time, but the relationship to the patients was intensified.
UNASSIGNED: While there was no indication for an increase in efficiency by using RPM systems, participating doctors indicated their potential for an enhanced interaction between doctor and patient. In particular, intensified interaction contact with patients with chronic diseases (e. g. COPD, long-COVID) could be of long-term interest and importance for doctors in ambulatory care.Trial Registration: DRKS00023553.

Osteocytes, as mechanosensitive cells residing within bone tissue, hold a pivotal role in averting the occurrence and progression of osteoporosis. The apoptosis of osteocytes induced by unloading is one of the contributing factors to osteoporosis, although the underlying molecular mechanisms have not been fully elucidated. PTH 1-34 is known to promote bone formation and inhibit bone loss by targeting osteoblasts and osteocytes. However, it is not known whether PTH 1-34 can inhibit osteocyte apoptosis under unloading conditions and the molecular mechanisms involved. In this study, we employed a Random Positioning Machine (RPM) to emulate unloading conditions and cultured MLO-Y4 osteocyte-like cells, in order to unravel the mechanisms through which PTH 1-34 constrains osteocyte apoptosis amidst unloading circumstances. Our findings revealed that PTH 1-34 activated autophagy while suppressing endoplasmic reticulum stress by curtailing the generation of reactive oxygen species (ROS) in MLO-Y4 osteocyte-like cells during unloading conditions. By shedding light on the osteoporosis triggered by skeletal unloading, this study contributes vital insights that may pave the way for the development of pharmacological interventions.

BACKGROUND: Multimodality is required for the treatment of breast cancer. Surgery, radiation (RT), and systemic therapy were traditionally used. Pharmacotherapy includes different drug mechanisms, such as chemotherapy, hormone therapy, and targeted therapies, alone or in combination with radiotherapy. While radiation offers numerous benefits, it also has certain harmful risks. such as cardiac and pulmonary toxicity, lymphedema, and secondary cancer. Modern radiation techniques have been developed to reduce organs at risk (OAR) doses.
METHODS: This study is a prospective feasibility trial conducted at the Fayium Oncology Center on patients with left breast cancer receiving adjuvant locoregional radiotherapy after either breast conservative surgery (BCS) or modified radical mastectomy (MRM). This study aimed to assess the proportion of patients who are fit both physically and intellectually to undergo breast radiotherapy using the deep inspiratory breath-holding (DIBH) technique, comparing different dosimetric outcomes between the 3D dimensional conformal with DIBH and 4D-CT IMRT plans of the same patient.
RESULTS: D95 of the clinical target volume (CTV) of the target is significantly higher in the 3D DIBH plan than in the IMRT plan, with an average of 90.812% vs. 86.944%. The dosimetry of the mean heart dose (MHD) in the 4D-CT IMRT plan was significantly lower than in the 3D conformal with the DIBH plan (2.6224 vs. 4.056 Gy, p < 0.0064), and no significant difference between the two plans regarding mean left anterior descending artery (LAD) (14.696 vs. 13.492 Gy, p < 0.58), maximum LAD (39.9 vs. 43.5 Gy, p < 0.35), and V20 of the ipsilateral lung (18.66% vs. 16.306%, p < 0.88) was observed. Internal mammary chain (IMC) irradiation was better in the 4D-CT IMRT plan.
CONCLUSIONS: Radiotherapy of the breast and chest wall with the 4D-CT IMRT technique appears not to be inferior to the 3D conformal with the DIBH technique and can be used as an alternative to the 3D conformal with the DIBH technique in patients meeting the exclusion criteria for performing the DIBH maneuver concerning coverage to target volumes or unacceptably high doses to OAR.