Machine-to-Machine Transfer Function in Deep Learning-Based Quantitative Ultrasound

A Transfer Function approach was recently demonstrated to mitigate data mismatches at the acquisition level for a single ultrasound scanner in deep learning (DL) based quantitative ultrasound (QUS). As a natural progression, we further investigate the transfer function approach and introduce a Machine-to-Machine (M2M) Transfer Function, which possesses the ability to mitigate data mismatches at a machine level, i.e., mismatches between two scanners over the same frequency band. This ability opens the door to unprecedented opportunities for reducing DL model development costs, enabling the combination of data from multiple sources or scanners, or facilitating the transfer of DL models between machines with ease. We tested the proposed method utilizing a SonixOne machine and a Verasonics machine. In the experiments, we used a L9-4 array and conducted two types of acquisitions to obtain calibration data: stable and free-hand, using two different calibration phantoms. Without the proposed calibration method, the mean classification accuracy when applying a model on data acquired from one system to data acquired from another system was approximately 50%, and the mean AUC was about 0.40. With the proposed method, mean accuracy increased to approximately 90%, and the AUC rose to the 0.99. Additional observations include that shifts in statistics for the z-score normalization had a significant impact on performance. Furthermore, the choice of the calibration phantom played an important role in the proposed method. Additionally, robust implementation inspired by Wiener filtering provided an effective method for transferring the domain from one machine to another machine, and it can succeed using just a single calibration view without the need for multiple independent calibration frames.Comment: 8 pages, 3 Figure

Can Ultrasound-Guided Femoral Vein Measurements Predict Spinal Anesthesia-Induced Hypotension in Non-Obstetric Surgery? A Prospective Observational Study

Background and objectives: To investigate whether ultrasound (US)-guided femoral vein (FV) and inferior vena cava (IVC) measurements obtained before spinal anesthesia (SA) can be utilized to predict SA-induced hypotension (SAIH) and to identify risk factors associated with SAIH in patients undergoing non-obstetric surgery under SA. Methods: This was a prospective observational study conducted between November 2021 and April 2022. The study included 95 patients over the age of 18 with an American Society of Anesthesiologists (ASA) physical status score of 1 or 2. The maximum and minimum diameters of FV and IVC were measured under US guidance before SA initiation, and the collapsibility index values of FV and IVC were calculated. Patients with and without SAIH were compared. Results: SAIH was observed in 12 patients (12.6%). Patients with and without SAIH were similar in terms of age [58 (IQR: 19–70) vs. 48 (IQR: 21–71; p = 0.081) and sex (males comprised 63.9% of the SAIH and 75.0% of the non-SAIH groups) (p = 0.533). According to univariate analysis, no significant relationship was found between SAIH and any of the FV or IVC measurements. Multiple logistic regression analysis revealed that having an ASA class of 2 was the only independent risk factor for SAIH development (p = 0.014), after adjusting for age, sex, and all other relevant parameters. Conclusions: There is not enough evidence to accept the feasibility of utilizing US-guided FV or IVC measurements to screen for SAIH development in patients undergoing non-obstetric surgery under SA. For this, multicenter studies with more participants are needed

Ultrastructural effects of topical beta-adrenergic antagonists and an alpha-adrenergic agonist on the rabbit cornea

PubMedID: 10202292In the present study the effects of ß-adrenergic antagonist and ?- adrenergic agonist drugs on rabbit corneas were evaluated in vivo by using transmission electron microscopy. Twenty-four New Zealand albino rabbits were divided into six groups according to the drug applied. The rabbits to which only balanced salt solution (BSS) or BSS and benzalkonium chloride (BAC) were applied were taken as the control groups. The other four groups consisted of the rabbits to which Timoptic 0.5%, Betagan 0.5%, Betoptic 0.5% and Iopidine 1% were applied, respectively. All of drugs were instilled topically twice daily for 6 weeks. In the BSS group, all layers of the cornea were ultrastructurally normal. In the BSS and BAC group slight epithelial and endothelial changes were found. However, in the other groups, loss of microvilli, increase in glycogen particles, nuclear indentation, widening of the intercellular spaces and cytoplasmic vacuolization in epithelium were observed. No significant abnormality was found in the basal lamina, stroma and Descemet's membrane. Slight ultrastructural changes were noted in the endothelium such as vacuolization due to dilatation of the endoplasmic reticulum cisternae and focal cytoplasmic lytic areas. The results of this study indicate that various ultrastructural changes occur in groups treated with antiglaucomatous drug and that topical treatment with timolol and apraclonidine for 6 weeks is more toxic to the rabbit cornea than levobunolol and betaxolol

Endo-VMFuseNet: A Deep Visual-Magnetic Sensor Fusion Approach for Endoscopic Capsule Robots

In the last decade, researchers and medical device companies have made major advances towards transforming passive capsule endoscopes into active medical robots. One of the major challenges is to endow capsule robots with accurate perception of the environment inside the human body, which will provide necessary information and enable improved medical procedures. We extend the success of deep learning approaches from various research fields to the problem of sensor fusion for endoscopic capsule robots in the case of asynchronous and asymmetric sensor data without any need of calibration between sensors. The results performed on real pig stomach datasets show that our method achieves high precision for both translational and rotational movements and contains various advantages over traditional sensor fusion techniques

Breeding of Şanlıurfa Pepper via Selection

Biber ülkemizin her bölgesinde yetiştiriciliği yapılan, taze veya çeşitli şekillerde işlenmiş olarakyaygın kullanıma sahip bir sebze türüdür. Türkiye 2.2 milyon ton biber üretimi ile dünyasıralamasında dördüncü sırada yer almaktadır. Bölgeler ve/veya yöreler kendine ait mikro klimalarasahip oldukları için bitki gelişimi ve verimin iyi olabilmesi oraya ait yeni çeşitlerin geliştirilmesigereklidir. Şanlıurfa'da biber üreticileri uzun yıllardır kendi tohumluklarını kendileri sağlamaktadır.Bu durum Şanlıurfa biber popülasyonunda genetik farklılığa neden olmuştur. Sulu tarımla birlikteyeni ticari biber çeşitlerinin bölgede üretilmeye başlamasıyla yeni çeşitler, yerli çeşitlerle yerdeğiştirmektedir. Gelecekte yeni çeşitlerin geliştirilebilmesi için genetik çeşitliliğe gereksinimolacaktır. Bu sebeple çeşitli çevresel streslere tolerans özelliklerine sahip genotiplerin toplanmasıgerekmektedir. Çalışmanın amacı, Şanlıurfa biber popülasyonundan, Güneydoğu Anadolu Bölgesiiklim şartlarına uygun genotiplerin seleksiyonudur. Güneydoğu Anadolu Bölgesinden genotiplerinseçimi, seçilen genotiplerin eşit şartlarda performasyonlarının denenmesi, saf hatların elde edilmesive tescilidir. Çalışma sonunda Güneydoğu Anadolu Bölgesinden seçilen genotiplerin verimdenemeleri bölgede gerçekleştirilmiş ve 6258,25 kg/da ile 1278-14 nolu saf hat İnan 3363 adı ileticari kaydı yapılmıştırPepper is widely produced in Turkey and consumed as fresh or after processing. Turkey, with its 2.2million tons of tomato production, is the world's 4th biggest producer of the world. Because ofregions and/or districts have their own microclimate, it is required to develop new varieties thatbelong there in order to better plant development and yield. This condition has resulted geneticallymodifications at Şanlıurfa pepper population. New commercial pepper varieties has begun to replaceand produced after irrigated farming. In the future, genetic varieties will be necessary for developingnew varieties. For this reason, it is required to collect environmentally tolerated genotypes. The aimof this study is to select some genotypes from Şanlıurfa pepper population that appropriate forSoutheastern Anatolia environmental conditions. Study has some stages: selection of temperaturetolerant pepper genotypes, evaluation of selected varieties performance, to acquire pure line,registration. As a result of the study, yield trials of selected genotypes has been done at region andregistration of 1278-14 pure line, with 6258.25kg/da yield of production, has been completed with acommercial name of Inan336

Stratification of the gut microbiota composition landscape across the alzheimer's disease continuum in a Turkish cohort

Alzheimer's disease (AD) is a heterogeneous disorder that spans a continuum with multiple phases, including preclinical, mild cognitive impairment, and dementia. Unlike for most other chronic diseases, human studies reporting on AD gut microbiota in the literature are very limited. With the scarcity of approved drugs for AD therapies, the rational and precise modulation of gut microbiota composition using diet and other tools is a promising approach to the management of AD. Such an approach could be personalized if an AD continuum can first be deconstructed into multiple strata based on specific microbiota features by using single or multiomics techniques. However, stratification of AD gut microbiota has not been systematically investigated before, leaving an important research gap for gut microbiota-based therapeutic approaches. Here, we analyze 16S rRNA amplicon sequencing of stool samples from 27 patients with mild cognitive impairment, 47 patients with AD, and 51 nondemented control subjects by using tools compatible with the compositional nature of microbiota. To stratify the AD gut microbiota community, we applied four machine learning techniques, including partitioning around the medoid clustering and fitting a probabilistic Dirichlet mixture model, the latent Dirichlet allocation model, and we performed topological data analysis for population-scale microbiome stratification based on the Mapper algorithm. These four distinct techniques all converge on Prevotella and Bacteroides stratification of the gut microbiota across the AD continuum, while some methods provided fine-scale resolution in stratifying the community landscape. Finally, we demonstrate that the signature taxa and neuropsychometric parameters together robustly classify the groups. Our results provide a framework for precision nutrition approaches aiming to modulate the AD gut microbiota

Outcomes of Chronic Total Occlusion Percutaneous Coronary Intervention After a Previous Failed Attempt

The impact of a previous failure on procedural techniques and outcomes of chronic total occlusion (CTO) percutaneous coronary intervention (PCI) has received limited study. We examined the clinical and angiographic characteristics and procedural outcomes of 9,393 patients who underwent 9,560 CTO PCIs at 42 United States and non-United States centers between 2012 and 2022. A total of 1,904 CTO lesions (20%) had a previous failed PCI attempt. Patients who underwent reattempt CTO PCI were more likely to have a family history of coronary artery disease (37% vs 31%, p30 CTO PCIs annually were more likely to achieve technical success in patients with previous failure. In conclusion, a previous failed CTO PCI attempt was associated with higher lesion complexity, longer procedure time, and lower technical success; however, the association with lower technical success did not remain significant in multivariable analysis

Preprocedural coronary computed tomography angiography in chronic total occlusion percutaneous coronary intervention: Insights from the PROGRESS-CTO registry

BACKGROUND: Preprocedural coronary computed tomography angiography (CCTA) can be useful in procedural planning for chronic total occlusion (CTO) percutaneous coronary intervention (PCI). METHODS: We examined the clinical, angiographic and procedural characteristics and outcomes of cases with vs. without preprocedural CCTA in PROGRESS-CTO (NCT02061436). Multivariable logistic regression was used to adjust for confounding factors. RESULTS: Of 7034 CTO PCI cases, preprocedural CCTA was used in 375 (5.3%) with increasing frequency over time. Patients with preprocedural CCTA had a higher prevalence of prior coronary artery bypass graft surgery (39% vs. 27%, p \u3c 0.001) and angiographically unfavorable characteristics including higher prevalence of proximal cap ambiguity (52% vs. 33%, p \u3c 0.001) and moderate/severe calcification (59% vs. 41%, p \u3c 0.001) compared with those without CCTA. CCTA helped resolve proximal cap ambiguity in 27%, identified significant calcium not seen on diagnostic angiography in 18%, changed estimated CTO length by \u3e5 mm in 10%, and was performed as part of initial coronary artery disease work up in 19%. CCTA cases had higher J-CTO (2.6 ± 1.2 vs. 2.3 ± 1.3, p \u3c 0.001) and PROGRESS-CTO (1.3 ± 1.0 vs. 1.2 ± 1.0 p = 0.027) scores. After adjusting for potential confounders, cases with preprocedural CCTA had similar technical success (odds ratio [OR]: 1.18, 95% confidence interval [CI], 0.83-1.67) and incidence of major adverse cardiovascular events (OR: 1.47, 95% CI, 0.72-3.00). CONCLUSION: Preprocedural CCTA was used in ~5% of CTO PCI cases. While CCTA may help with procedural planning, especially in complex cases, technical success and MACE were similar with or without CCTA