PubMed İndeksli Yayın KoleksiyonuPubMed Indexed Publications Collectionhttps://hdl.handle.net/20.500.12846/1192024-03-29T01:03:51Z2024-03-29T01:03:51ZThe prolonged effect of Kinesio Taping on joint torque and muscle activityKulli, Hilal DenizogluKarabulut, DeryaArslan, Yunus Ziyahttps://hdl.handle.net/20.500.12846/7092023-03-12T16:20:34Z2022-01-01T00:00:00ZThe prolonged effect of Kinesio Taping on joint torque and muscle activity
Kulli, Hilal Denizoglu; Karabulut, Derya; Arslan, Yunus Ziya
PurposeAlthough Kinesio Taping has been extensively used, evidence about the effect of Kinesio Taping is still insufficient. The aim is to determine the effect of Kinesio Taping on elbow joint torque and muscle activity in time and frequency domains.Materials and MethodsThirty-eight healthy subjects were (27 females and 11 males) randomly divided into control and Kinesio Taping groups. Kinesio Taping was applied over biceps brachii muscle in Kinesio Taping group, whereas no taping was applied to control group. Maximum elbow joint torque and electromyography activity in time and frequency domains were assessed during maximum isometric contraction of biceps brachii muscle at baseline, after 10 min, 30 min, and 24 h. Repeated measure ANOVA and mixed ANOVA tests were used for in-group and between-group comparisons, respectively.ResultsElbow joint torques among four assessment sessions were statistically altered in Kinesio Taping group and greater in Kinesio Taping group than in control group (F(3,57)= 3.317, p = 0.026, eta p2 = 0.149; F(3,108)=3.325, p = 0.022, eta p2 = 0.085; respectively). No difference was found in time domain muscle activity among assessment sessions in each group and comparison of groups (p > 0.05). Low-gamma band activity was changed among assessment sessions in Kinesio Taping group (F(3,57)= 6.946, p < 0.001, eta p2 = 0.268) while group x time interaction was not determined.ConclusionsKinesio Taping may influence joint torque of elbow more than without Kinesio Taping condition in 24th hour but the interpretation of this effect as a muscle strength enhancement compared with baseline can be arguable. Even if Kinesio Taping could not affect muscle activity in time domain, low-gamma band activity which is closely related to somatosensorial input may reach highest magnitude 24 h after Kinesio Taping.
2022-01-01T00:00:00ZHow an ACE2 mimicking epitope-MIP nanofilm recognizes template-related peptides and the receptor binding domain of SARS-CoV-2Zhang, XiaorongWaffo, Armel T.Yarman, AysuKovacs, NorbertBognar, ZsofiaWollenberger, UllaEl-Sherbiny, Ibrahim M.Hassan, Rabeay Y. A.Bier, Frank F.Gyurcsanyi, Robert EZebger, IngoScheller, Frieder W.https://hdl.handle.net/20.500.12846/7082023-03-12T16:13:21Z2022-01-01T00:00:00ZHow an ACE2 mimicking epitope-MIP nanofilm recognizes template-related peptides and the receptor binding domain of SARS-CoV-2
Zhang, Xiaorong; Waffo, Armel T.; Yarman, Aysu; Kovacs, Norbert; Bognar, Zsofia; Wollenberger, Ulla; El-Sherbiny, Ibrahim M.; Hassan, Rabeay Y. A.; Bier, Frank F.; Gyurcsanyi, Robert E; Zebger, Ingo; Scheller, Frieder W.
Here we aim to gain a mechanistic understanding of the formation of epitope-imprinted polymer nanofilms using a non-terminal peptide sequence, i.e. the peptide GFNCYFP (G485 to P491) of the SARS-CoV-2 receptor binding domain (RBD). This epitope is chemisorbed on the gold surface through the central cysteine 488 followed by the electrosynthesis of a similar to 5 nm thick polyscopoletin film around the surface confined templates. The interaction of peptides and the parent RBD and spike protein with the imprinted polyscopoletin nanofilm was followed by electrochemical redox marker gating, surface enhanced infrared absorption spectroscopy and conductive AFM. Because the use of non-terminal epitopes is especially intricate, here we characterize the binding pockets through their interaction with 5 peptides rationally derived from the template sequence, i.e. implementing central single amino acid mismatch as well as elongations and truncations at its C- and N- termini. Already a single amino acid mismatch, i.e. the central Cys488 substituted by a serine, results in ca. 15-fold lower affinity. Further truncation of the peptides to tetrapeptide (EGFN) and hexapeptide (YFPLQS) results also in a significantly lower affinity. We concluded that the affinity towards the different peptides is mainly determined by the four amino acid motif CYFP present in the sequence of the template peptide. A higher affinity than that for the peptides is found for the parent proteins RBD and spike protein, which seems to be due to out of cavity effects caused by their larger footprint on the nanofilm surface.
2022-01-01T00:00:00ZClassification of breast cancer histopathological images using DenseNet and transfer learningWakili, Musa AdamuShehu, Harisu AbdullahiSharif, Md. HaidarSharif, Md. Haris UddinUmar, AbubakarKusetoğulları, Hüseyinİnce, İbrahim FurkanUyaver, Şahinhttps://hdl.handle.net/20.500.12846/7022023-02-23T08:43:24Z2022-01-01T00:00:00ZClassification of breast cancer histopathological images using DenseNet and transfer learning
Wakili, Musa Adamu; Shehu, Harisu Abdullahi; Sharif, Md. Haidar; Sharif, Md. Haris Uddin; Umar, Abubakar; Kusetoğulları, Hüseyin; İnce, İbrahim Furkan; Uyaver, Şahin
Breast cancer is one of the most common invading cancers in women. Analyzing breast cancer is nontrivial and may lead to disagreements among experts. Although deep learning methods achieved an excellent performance in classification tasks including breast cancer histopathological images, the existing state-of-the-art methods are computationally expensive and may overfit due to extracting features from in-distribution images. In this paper, our contribution is mainly twofold. First, we perform a short survey on deep-learning-based models for classifying histopathological images to investigate the most popular and optimized training-testing ratios. Our findings reveal that the most popular training-testing ratio for histopathological image classification is 70%: 30%, whereas the best performance (e.g., accuracy) is achieved by using the training-testing ratio of 80%: 20% on an identical dataset. Second, we propose a method named DenTnet to classify breast cancer histopathological images chiefly. DenTnet utilizes the principle of transfer learning to solve the problem of extracting features from the same distribution using DenseNet as a backbone model. The proposed DenTnet method is shown to be superior in comparison to a number of leading deep learning methods in terms of detection accuracy (up to 99.28% on BreaKHis dataset deeming training-testing ratio of 80%: 20%) with good generalization ability and computational speed. The limitation of existing methods including the requirement of high computation and utilization of the same feature distribution is mitigated by dint of the DenTnet.
2022-01-01T00:00:00ZProduction of rare earth element oxide powders by solution combustion: a new approach for recycling of NdFeB magnetsKaya, Elif EmilStopic, SreckoGürmen, SebahattinFriedrich, Berndhttps://hdl.handle.net/20.500.12846/7002022-12-05T08:24:13Z2022-01-01T00:00:00ZProduction of rare earth element oxide powders by solution combustion: a new approach for recycling of NdFeB magnets
Kaya, Elif Emil; Stopic, Srecko; Gürmen, Sebahattin; Friedrich, Bernd
NdFeB magnets are employed in various technological applications due to their outstanding magnetic properties, such as high maximum energy product, high remanence and high coercivity. Production of NdFeB has gathered more interest, therefore the demand for rare earth elements (REEs) has continuously increased. The recovery of REEs has become essential to satisfy this demand in recent years. In the present study, a promising flowsheet is proposed for REEs recovery from NdFeB magnets, as follows: (1) acid baking, (2) employment of ultrasound-assisted water leaching, (3) the production of rare earth oxides (RE oxides) by a solution combustion method, and (4) a calcination process. There are several problems in conventional precipitation such as loss of a high amount of metal during precipitation and use of a high amount of precipitation agents. It is worth mentioning that the consumed precipitation agents in the solution are not easily recyclable. This study aims especially to investigate the production of RE oxides from recycled NdFeB magnets by solution combustion as an alternative to conventional precipitation methods. In this way, impurities that may have come to the system from the precipitation agents were prevented. Moreover, in the production of RE oxides via the above-mentioned method, precipitation agents and filtration steps were not necessary.
2022-01-01T00:00:00Z