The quality of cranial ultrasound has improved over time, with advancing technology leading to higher resolution, faster image processing, digital display, and back-up. However, some brain lesions may remain difficult to characterize: since higher frequencies result in greater spatial resolution, the use of additional transducers may overcome some of these limitations. The very high-frequency transducers (18-5 MHz) are currently employed for small parts and lung ultrasound. Here we report the first case series comparing the very high-frequency probes (18-5 MHz) with standard micro-convex probes (8-5 MHz) for cranial ultrasound in preterm infants. In this case series, we compared cranial ultrasound images obtained with a micro-convex transducer (8-5 MHz) and those obtained with a very high-frequency (18-5 MHz) linear array transducer in 13 preterm infants ≤ 32 weeks gestation (9 with cerebral abnormalities and 4 with normal findings). Ultrasound examinations using the very high-frequency linear transducer and the standard medium-frequency micro-convex transducer were performed simultaneously. We also compared ultrasound findings with brain MRI images obtained at term corrected age. Ultrasound images obtained with the very high-frequency (18-5 MHz) transducer showed high quality and accuracy. Notably, despite their higher frequency and expected limited penetration capacity, brain size is small enough in preterm infants, so that brain structures are close to the transducer, allowing for complete evaluation.    Conclusion: We propose the routine use of very high-frequency linear probes as a complementary scanning modality for cranial ultrasound in preterm infants ≤ 32 weeks gestation. What is Known: • Brain lesions in preterm infants may remain insufficiently defined through conventional cranial ultrasound scan. • Higher frequency probes  offer better spatial resolution but have a narrower filed of exploration and limited penetration capacity. What is New: • Very high-frequency probes were compared with standard medium-frequency probes for cranial ultrasound in infants  ≤ 32 weeks\' gestation. • Thanks to the smaller skull size of preterm infants, the new very high-frequency transducers allowed a complete and accurate evaluation.

The spread of the novel coronavirus 2019 (COVID-19) has caused a global pandemic. The disease has spread rapidly, and research shows that COVID-19 can induce long-lasting cardiac damage. COVID-19 can result in elevated cardiac biomarkers indicative of acute cardiac injury, and research utilizing echocardiography has shown that there is mechanical dysfunction in these patients as well, especially when observing the isovolumic, systolic, and diastolic portions of the cardiac cycle. The purpose of this study was to present two case studies on COVID-19 positive patients who had their cardiac mechanical function assessed every day during the acute period to show that cardiac function in these patients was altered, and the damage occurring can change from day-to-day. Participant 1 showed compromised cardiac function in the systolic time, diastolic time, isovolumic time, and the calculated heart performance index (HPI), and these impairments were sustained even 23 days post-symptom onset. Furthermore, Participant 1 showed prolonged systolic periods that lasted longer than the diastolic periods, indicative of elevated pulmonary artery pressure. Participant 2 showed decreases in systole and consequently, increases in HPI during the 3 days post-symptom onset, and these changes returned to normal after day 4. These results showed that daily observation of cardiac function can provide detailed information about the overall mechanism by which cardiac dysfunction is occurring and that COVID-19 can induce cardiac damage in unique patterns and thus can be studied on a case-by-case basis, day-to-day during infection. This could allow us to move toward more personalized cardiovascular medical treatment.

BACKGROUND: Paralabral cysts are a rare cause of shoulder pain. Linear ultrasound transducers are often used for musculoskeletal evaluation and intervention. However, the use of linear transducer is limited when the target structure is located deep and blocked by bony barriers, as is the case of paralabral ganglion cysts.
OBJECTIVE: This case report aims to describe a beneficial role of using a convex transducer on the evaluation and ultrasonography-guided intervention of paralabral cysts below the acromion.
METHODS: Two patients visiting the outpatient clinic of Physical Medicine and Rehabilitation complained of severe pain during shoulder movement. Ultrasound scans with linear transducer detected rotator cuff lesions. Shoulder magnetic resonance imaging was done because of the persistent pain despite therapeutic interventions for the rotator cuff lesion, and confirmed paralabral cysts. Although a linear array transducer could not visualize the cystic lesion but could only perform suprascapular nerve block and intra-articular injection, the use of a convex array transducer improved the visualization of the cystic lesion which we treated using ultrasound-guided aspiration and intra-cystic injection. Visual analog scale and Shoulder Pain and Disability Index were checked to assess the treatment effect of each intervention. The intra-cystic injection with aspiration and intra-articular injection showed minimal to moderate improvement of pain score.
CONCLUSIONS: In pain related to shoulder movement, especially pain that continues despite appropriate treatment for rotator cuff lesions, ultrasound diagnosis of paralabral ganglion cysts using convex transducers will improve the diagnostic value and accuracy of intervention.

暂无摘要。

OBJECTIVE: In chronic lymphocytic leukemia (CLL), lack of expression or dysregulation of some special miRs disrupts apoptosis of malignant cells; thereby miR expression can enhance cell proliferation, disease progression and decrease patient survival.
RESULTS: 30 CLL patients and 20 healthy individuals participated in the study. RNA was extracted to evaluate the expression of miR-125, miR-223, BCL-2 and signal transducer and transcription 3 activator (STAT3) genes; quantitative Real Time- PCR (Q-RT-PCR) was performed. MiR-125a and miR-223 expression decreased in the patients compared to the control group (P-Value:0.001). BCL-2 and STAT3 which are the target genes of these two miRs, showed increased expression, in the patients compared to the control subjects (P-Value: 0.001 and P-Value: 0.64 respectively). A significant reverse relationship was found between miR-125a and BCl-2 expression and WBC count. Significantly, miR-223 expression was associated with smoking in patients (P-Value: 0.007). Also, these miRs may have regulatory effects by controlling white blood cell (WBC) production based on the inverse correlation with WBC count and hemoglobin (Hb) concentration. Finally, miR-223 can be used as a prognostic factor in CLL patients; miR-125a may be useful for evaluating the therapeutic approaches based on the inverse link with BCl-2.

The severe acute respiratory syndrome novel coronavirus-2 pandemic has established a new set of challenges to health care delivery. Remotely monitored physiologic sensors on implantable cardiac devices can provide insight into the differential diagnosis of dyspnea in the heart failure population. We report on a unique pattern of sensor deviations that seem to occur specifically with severe acute respiratory syndrome novel coronavirus-2 infection.

Iran has experienced a severe drought during the past two decades. Increasing water demand and decreasing available water resources have led the country to critical conflicts, particularly in shared watersheds. In these basins, the precise measurement of releasing water from upstream to downstream can be a key data for resolving water conflicts. The Iranian Ministry of Energy (MOE) makes the streamflow measurements through regional water administrative offices, mainly using the classical rating curve (RC) method. The documented measurements of runoff by adjacent offices usually present different estimations of the water resources, due to high uncertainties of the RC approach. Fluvial acoustic tomography (FAT) is a reliable technology for continuously monitoring streamflow, which can be implemented to solve this problem of shared basins. In this study, FAT is applied to the Zayanderud basin, an Iranian shared watershed and its results are compared with the RC methods. The main terms of FAT streamflow measurement uncertainty are velocity resolution component, and the selected flow angle between the stream direction and acoustic transmission path. Therefore, a new equation is proposed to carefully choose accurate angles for different river widths to decrease FAT measurement error in this paper. The obtained results show that the measured streamflow by FAT and RC are 9.89 m3/s and 10.3 m3/s, respectively, and the largest possible error of FAT is less than 15%.

OBJECTIVE: In the Multisensor Chronic Evaluation in Ambulatory Heart Failure Patients study, a novel algorithm for heart failure (HF) monitoring was implemented. The HeartLogic (Boston Scientific) index combines data from multiple implantable cardioverter defibrillator (ICD)-based sensors and has proved to be a sensitive and timely predictor of impending HF decompensation. The remote monitoring of HF patients by means of HeartLogic has never been described in clinical practice. We report post-implantation data collected from sensors, the combined index, and their association with clinical events during follow-up in a group of patients who received a HeartLogic-enabled device in clinical practice.
RESULTS: Patients with ICD and cardiac resynchronization therapy ICD were remotely monitored. In December 2017, the HeartLogic feature was activated on the remote monitoring platform, and multiple ICD-based sensor data collected since device implantation were made available: HeartLogic index, heart rate, heart sounds, thoracic impedance, respiration, and activity. Their association with clinical events was retrospectively analysed. Data from 58 patients were analysed. During a mean follow-up of 5 ± 3 months, the HeartLogic index crossed the threshold value (set by default to 16) 24 times (over 24 person-years, 0.99 alerts/patient-year) in 16 patients. HeartLogic alerts preceded five HF hospitalizations and five unplanned in-office visits for HF. Symptoms or signs of HF were also reported at the time of five scheduled visits. The median early warning time and the time spent in alert were longer in the case of hospitalizations than in the case of minor events of clinical deterioration of HF. HeartLogic contributing sensors detected changes in heart sound amplitude (increased third sound and decreased first sound) in all cases of alerts. Patients with HeartLogic alerts during the observation period had higher New York Heart Association class (P = 0.025) and lower ejection fraction (P = 0.016) at the time of activation.
CONCLUSIONS: Our retrospective analysis indicates that the HeartLogic algorithm might be useful to detect gradual worsening of HF and to stratify risk of HF decompensation.

Despite having notable advantages over established machine learning methods for time series analysis, reservoir computing methods, such as echo state networks (ESNs), have yet to be widely used for practical data mining applications. In this paper, we address this deficit with a case study that demonstrates how ESNs can be trained to predict disease labels when stimulated with movement data. Since there has been relatively little prior research into using ESNs for classification, we also consider a number of different approaches for realising input-output mappings. Our results show that ESNs can carry out effective classification and are competitive with existing approaches that have significantly longer training times, in addition to performing similarly with models employing conventional feature extraction strategies that require expert domain knowledge. This suggests that ESNs may prove beneficial in situations where predictive models must be trained rapidly and without the benefit of domain knowledge, for example on high-dimensional data produced by wearable medical technologies. This application area is emphasized with a case study of Parkinson\'s disease patients who have been recorded by wearable sensors while performing basic movement tasks.

The purpose of the present study was to test an idea of and describe a concept of a novel method of detecting defects related to horizontal nonuniformities in ultrasound equipment. The method is based on the analysis of ultrasound images collected directly from the clinical workflow. In total over 31000 images from three ultrasound scanners from two vendors were collected retrospectively from a database. An algorithm was developed and applied to the images, 150 at a time, for detection of systematic dark regions in the superficial part of the images. The result was compared with electrical measurements (FirstCall) of the transducers, performed at times when the transducers were known to be defective. The algorithm made similar detection of horizontal nonuniformities for images acquired at different time points over long periods of time. The results showed good subjective visual agreement with the available electrical measurements of the defective transducers, indicating a potential use of clinical images for early and automatic detection of defective transducers, as a complement to quality control.