A Biomechanical Analysis of the Interlock Suture and a Modified Kessler-Loop Lock Flexor Tendon Suture

OBJECTIVE: In this work, we attempted to develop a modified single-knot Kessler-loop lock suture technique and compare the biomechanical properties associated with this single-knot suture technique with those associated with the conventional modified Kessler and interlock suture techniques. METHODS: In this experiment, a total of 18 porcine flexor digitorum profundus tendons were harvested and randomly divided into three groups. The tendons were transected and then repaired using three different techniques, including modified Kessler suture with peritendinous suture, interlock suture with peritendinous suture, and modified Kessler-loop lock suture with peritendinous suture. Times required for suturing were recorded and compared among groups. The groups were also compared with respect to 2-mm gap load, ultimate failure load, and gap at failure. RESULTS: For tendon repair, compared with the conventional modified Kessler suture technique, the interlock and modified Kessler-loop lock suture techniques resulted in significantly improved biomechanical properties. However, there were no significant differences between the interlock and modified Kessler-loop lock techniques with respect to biomechanical properties, gap at failure, and time required. CONCLUSIONS: The interlock and modified Kessler-loop lock techniques for flexor tendon sutures produce similar mechanical characteristics in vitro

A review on the mechanical metamaterials and their applications in the field of biomedical engineering

Metamaterials are a group of materials/structures which possess novel behaviors not existing in nature. The metamaterials include electromagnetic metamaterials, acoustic metamaterials, mechanical metamaterials, etc. among which the mechanical metamaterials are widely used in the field of biomedical engineering. The mechanical metamaterials are the ones that possess special mechanical behaviors, e.g., lightweight, negative Poisson’s ratio, etc. In this paper, the commonly used mechanical metamaterials are reviewed and their applications in the field of biomedical engineering, especially in bone tissue engineering and vascular stent, are discussed. Finally, the future perspectives of this field are given

Prediction of protein assemblies, the next frontier: The CASP14-CAPRI experiment

We present the results for CAPRI Round 50, the fourth joint CASP-CAPRI protein assembly prediction challenge. The Round comprised a total of twelve targets, including six dimers, three trimers, and three higher-order oligomers. Four of these were easy targets, for which good structural templates were available either for the full assembly, or for the main interfaces (of the higher-order oligomers). Eight were difficult targets for which only distantly related templates were found for the individual subunits. Twenty-five CAPRI groups including eight automatic servers submitted ~1250 models per target. Twenty groups including six servers participated in the CAPRI scoring challenge submitted ~190 models per target. The accuracy of the predicted models was evaluated using the classical CAPRI criteria. The prediction performance was measured by a weighted scoring scheme that takes into account the number of models of acceptable quality or higher submitted by each group as part of their five top-ranking models. Compared to the previous CASP-CAPRI challenge, top performing groups submitted such models for a larger fraction (70–75%) of the targets in this Round, but fewer of these models were of high accuracy. Scorer groups achieved stronger performance with more groups submitting correct models for 70–80% of the targets or achieving high accuracy predictions. Servers performed less well in general, except for the MDOCKPP and LZERD servers, who performed on par with human groups. In addition to these results, major advances in methodology are discussed, providing an informative overview of where the prediction of protein assemblies currently stands.Cancer Research UK, Grant/Award Number: FC001003; Changzhou Science and Technology Bureau, Grant/Award Number: CE20200503; Department of Energy and Climate Change, Grant/Award Numbers: DE-AR001213, DE-SC0020400, DE-SC0021303; H2020 European Institute of Innovation and Technology, Grant/Award Numbers: 675728, 777536, 823830; Institut national de recherche en informatique et en automatique (INRIA), Grant/Award Number: Cordi-S; Lietuvos Mokslo Taryba, Grant/Award Numbers: S-MIP-17-60, S-MIP-21-35; Medical Research Council, Grant/Award Number: FC001003; Japan Society for the Promotion of Science KAKENHI, Grant/Award Number: JP19J00950; Ministerio de Ciencia e Innovación, Grant/Award Number: PID2019-110167RB-I00; Narodowe Centrum Nauki, Grant/Award Numbers: UMO-2017/25/B/ST4/01026, UMO-2017/26/M/ST4/00044, UMO-2017/27/B/ST4/00926; National Institute of General Medical Sciences, Grant/Award Numbers: R21GM127952, R35GM118078, RM1135136, T32GM132024; National Institutes of Health, Grant/Award Numbers: R01GM074255, R01GM078221, R01GM093123, R01GM109980, R01GM133840, R01GN123055, R01HL142301, R35GM124952, R35GM136409; National Natural Science Foundation of China, Grant/Award Number: 81603152; National Science Foundation, Grant/Award Numbers: AF1645512, CCF1943008, CMMI1825941, DBI1759277, DBI1759934, DBI1917263, DBI20036350, IIS1763246, MCB1925643; NWO, Grant/Award Number: TOP-PUNT 718.015.001; Wellcome Trust, Grant/Award Number: FC00100

Impact of AlphaFold on Structure Prediction of Protein Complexes: The CASP15-CAPRI Experiment

We present the results for CAPRI Round 54, the 5th joint CASP-CAPRI protein assembly prediction challenge. The Round offered 37 targets, including 14 homo-dimers, 3 homo-trimers, 13 hetero-dimers including 3 antibody-antigen complexes, and 7 large assemblies. On average ~70 CASP and CAPRI predictor groups, including more than 20 automatics servers, submitted models for each target. A total of 21941 models submitted by these groups and by 15 CAPRI scorer groups were evaluated using the CAPRI model quality measures and the DockQ score consolidating these measures. The prediction performance was quantified by a weighted score based on the number of models of acceptable quality or higher submitted by each group among their 5 best models. Results show substantial progress achieved across a significant fraction of the 60+ participating groups. High-quality models were produced for about 40% for the targets compared to 8% two years earlier, a remarkable improvement resulting from the wide use of the AlphaFold2 and AlphaFold-Multimer software. Creative use was made of the deep learning inference engines affording the sampling of a much larger number of models and enriching the multiple sequence alignments with sequences from various sources. Wide use was also made of the AlphaFold confidence metrics to rank models, permitting top performing groups to exceed the results of the public AlphaFold-Multimer version used as a yard stick. This notwithstanding, performance remained poor for complexes with antibodies and nanobodies, where evolutionary relationships between the binding partners are lacking, and for complexes featuring conformational flexibility, clearly indicating that the prediction of protein complexes remains a challenging problem

Impact of AlphaFold on structure prediction of protein complexes: The CASP15-CAPRI experiment

We present the results for CAPRI Round 54, the 5th joint CASP-CAPRI protein assembly prediction challenge. The Round offered 37 targets, including 14 homodimers, 3 homo-trimers, 13 heterodimers including 3 antibody-antigen complexes, and 7 large assemblies. On average ~70 CASP and CAPRI predictor groups, including more than 20 automatics servers, submitted models for each target. A total of 21 941 models submitted by these groups and by 15 CAPRI scorer groups were evaluated using the CAPRI model quality measures and the DockQ score consolidating these measures. The prediction performance was quantified by a weighted score based on the number of models of acceptable quality or higher submitted by each group among their five best models. Results show substantial progress achieved across a significant fraction of the 60+ participating groups. High-quality models were produced for about 40% of the targets compared to 8% two years earlier. This remarkable improvement is due to the wide use of the AlphaFold2 and AlphaFold2-Multimer software and the confidence metrics they provide. Notably, expanded sampling of candidate solutions by manipulating these deep learning inference engines, enriching multiple sequence alignments, or integration of advanced modeling tools, enabled top performing groups to exceed the performance of a standard AlphaFold2-Multimer version used as a yard stick. This notwithstanding, performance remained poor for complexes with antibodies and nanobodies, where evolutionary relationships between the binding partners are lacking, and for complexes featuring conformational flexibility, clearly indicating that the prediction of protein complexes remains a challenging problem

Methionine Regulates mTORC1 via the T1R1/T1R3-PLCβ-Ca2+-ERK1/2 Signal Transduction Process in C2C12 Cells

The mammalian target of rapamycin complex 1 (mTORC1) integrates amino acid (AA) availability to support protein synthesis and cell growth. Taste receptor type 1 member (T1R) is a G protein-coupled receptor that functions as a direct sensor of extracellular AA availability to regulate mTORC1 through Ca2+ stimulation and extracellular signal–regulated kinases 1 and 2 (ERK1/2) activation. However, the roles of specific AAs in T1R1/T1R3-regulated mTORC1 are poorly defined. In this study, T1R1 and T1R3 subunits were expressed in C2C12 myotubes, and l-AA sensing was accomplished by T1R1/T1R3 to activate mTORC1. In response to l-AAs, such as serine (Ser), arginine (Arg), threonine (Thr), alanine (Ala), methionine (Met), glutamine (Gln), and glycine (Gly), Met induced mTORC1 activation and promoted protein synthesis. Met also regulated mTORC1 via T1R1/T1R3-PLCβ-Ca2+-ERK1/2 signal transduction. Results revealed a new role for Met-regulated mTORC1 via an AA receptor. Further studies should be performed to determine the role of T1R1/T1R3 in mediating extracellular AA to regulate mTOR signaling and to reveal its mechanism

A Modified Flexor Tendon Suture Technique Combining Kessler and Loop Lock Flexor Tendon Sutures

OBJECTIVES: In the present study, a novel single knot tenorrhaphy was developed by combining the modified Kessler flexor tendon suture (MK) with the loop lock technique. METHODS: A total of 48 porcine flexor digitorum profundus tendons were collected and randomly divided into six groups. The tendons were transversely cut and then repaired using six different techniques, the MK method, double knot Kessler-loop lock flexor tendon suture (DK), and single knot Kessler-loop lock flexor tendon suture (SK), each in combination with the epitendinous suture (P), and the same three techniques without P. Furthermore, by performing the load-to-failure tests, the biomechanical properties and the time taken to complete a repair, for each tenorrhaphy, were assessed. RESULTS: Compared to the MK+P method, DK+P was more improved, thereby enhancing the ultimate tensile strength. The SK+P method, which required fewer knots than DK+P, was easier to perform. Moreover, the SK+P repair increased the force at a 2-mm gap formation, while requiring lesser knots than DK+P. CONCLUSION: As opposed to the traditional MK+P method, the SK+P method was improved and exhibited better biomechanical properties, which may facilitate early mobilization after the repair

A Biomechanical Analysis of the Interlock Suture and a Modified Kessler-Loop Lock Flexor Tendon Suture

OBJECTIVE: In this work, we attempted to develop a modified single-knot Kessler-loop lock suture technique and compare the biomechanical properties associated with this single-knot suture technique with those associated with the conventional modified Kessler and interlock suture techniques. METHODS: In this experiment, a total of 18 porcine flexor digitorum profundus tendons were harvested and randomly divided into three groups. The tendons were transected and then repaired using three different techniques, including modified Kessler suture with peritendinous suture, interlock suture with peritendinous suture, and modified Kessler-loop lock suture with peritendinous suture. Times required for suturing were recorded and compared among groups. The groups were also compared with respect to 2-mm gap load, ultimate failure load, and gap at failure. RESULTS: For tendon repair, compared with the conventional modified Kessler suture technique, the interlock and modified Kessler-loop lock suture techniques resulted in significantly improved biomechanical properties. However, there were no significant differences between the interlock and modified Kessler-loop lock techniques with respect to biomechanical properties, gap at failure, and time required. CONCLUSIONS: The interlock and modified Kessler-loop lock techniques for flexor tendon sutures produce similar mechanical characteristics in vitro