Electroadhesive grippers can be used to pick up a wide range of materials, and those with variable stiffness functionality can increase load capacity and strength. This paper proposes an electroadhesive gripper (VSEAF) with variable stiffness function and a simple construction based on low melting point alloys (LMPAs) with active form adaptation through pneumatic driving. Resistance wires provide active changing stiffness. For a case study, a three-fingered gripper was designed with three electroadhesive fingers of varied stiffness. It is envisaged that these electroadhesive grippers with variable stiffness would extend the preparation process and boost the use of electroadhesion in soft robot applications. To operate safely in unstructured environments and in collaboration with humans, a new generation of robots must be created; therefore, soft robots comprised of soft materials invented recently have a high degree of deformation, and their interactions with humans and objects are more flexible and compliant than those of traditional stiff robots ,2,3. In Electroadhesion (EA) is a promising adhesion mechanism and material handling technique that is typically powered by a high voltage (commonly in the range of 0.2 to 20 kilovolts) between pairs of electrodes ,9,10,11.EA requires close contact with an object in order to generate sufficient gripping force. EA with shape adaptation characteristics can increase gripping efficiency. Guo et al. proposed a morphologically adaptive EA end effector, the PneuEA gripper , which wTo address the lack of rigidity and low load capacity of soft robots, researchers proposed the notion of variable stiffness. Soft robots equipped with variable stiffness functionality can boost safety when considering physical human–robot cooperation ,13 and lElectrostatic adhesion (EA) is generated by applying a high voltage  across pairs of electrodes embedded in a dielectric material. This high electric field produces an electrically controllable adhesion force on conductive, semi-conductive, and insulating substrates . EA withTo address the soft robots’ lack of rigidity and limited load capacity, this paper proposes an electroadhesive gripper with variable stiffness and simple construction (VSEAF) based on low melting point alloys (LMPAs) with active form adaptation via a pneumatic drive. A soft pneumatic gripper of electrostatic adsorption with a variable stiffness function was proposed in this work to meet the requirement of good adaptability between the electro-adhesive gripper and substrate. The contents are organized as follows: the specifics of the VSEAG’s design and manufacture are discussed in We intend to develop a variable stiffness electroadhesive finger (VSEAF) that can adjust its stiffness during pneumatic actuation in order to conform to different shapes. The soft pneumatic finger is constructed with an inflated chamber, low melting point alloys , and electric resistance wires  for this purpose see . In ordeThe VSEAF exhibits a rigid state when low melting point alloys are solid and a soft state when low melting point alloys are liquid. Low-melting-point alloys can be used to generate EA force in order to boost the VSEAF’s grasping capacity, and the electric resistance wire can be used to heat low temperatures. As a result, VSEAF can not only grip objects while pneumatically actuated, but it can also generate electroadhesive force to grasp objects of different shapes and sizes. The article’s gripper is pneumatic, and its mobility is controlled by a pneumatic system. This gripper provides a smooth action due to its usage of a pneumatic triplet.The VSEAF workflow is as follows: VSEAF approaches the object to be grasped, the resistance wire is heated by electricity, the gripper enters a state of low stiffness, and the VSEAF chamber is inflated and bent to conform to the object to be grasped. The power to the electric resistance wire is then turned off, and when the low melting point alloy has cooled and solidified, the VSEAF will be in a rigid state. Lastly, a high voltage is given to the low melting point alloy to initiate electrostatic adsorption, allowing the gripper to grasp and hoist the clamped object with stability and dependability.The low-melting-point alloys are used to create a soft pneumatic gripper and a variable stiffness EA pad for the VSEAF device. The proposed method for manufacturing the VSEAF grippers is simple, as shown in Moulding the variable stiffness EA pad.Molding a pneumatic soft gripper. Using a 3D printer  and PLA filament with a 3 mm diameter, two moulds were created in three dimensions. Before filling these two moulds, equal amounts of silicone Ecoflex 30  were blended and weighed. The Ecoflex mixture was then degassed for twenty minutes. The mould was then cured in a 50 °C oven for two hours.Integration of the EA pad with the soft pneumatic gripper. The soft pneumatic gripper was affixed to the variable stiffness EA pad using a silicone Ecoflex 30 combination, and the assembly was cured in a 50 °C oven for two hours. We developed tangential EA force measurement equipment, as seen in For the fabrication repeatability test, EA pads with three unique spacings were fabricated three times; notably, EA pads with three unique spacings were created three times for the fabrication repeatability test, resulting in the manufacturing of nine EA pads. Three tests were conducted for each EA pad, and these experiments were conducted in a clean, constrained setting. In addition, tests were done at a temperature of 22.6 °C ± 0.1 °C, relative humidity of 55% ± 1%, and ambient pressure of 1025.5 hPa ± 0.2 hPa using a weather station. There was a maximum relative difference of 4.5% in the average tangential EA forces collected from the nine EA pads, as shown in As illustrated in the insets of The test results for tangential and normal EA forces are shown in As electrode spacing rises, so does the breakdown voltage of the EA pad; for example, electrode spacings of 2 mm, 3 mm, and 4 mm corresponded to breakdown voltages of 3.2 kV, 3.8 kV, and 4.4 kV, respectively. Clearly, in a certain range, an EA pad may produce a larger EA force with a wider electrode spacing, but to achieve the same EA force, an EA with a wide electrode spacing requires a higher excitation voltage. Similar to how stronger EA forces need more costly high voltage amplification equipment and higher prices, a higher voltage also incurs more safety risks; therefore, increasing the electrode spacing is not the sole approach to enhance adsorption capacity. The maximum tangential force generated by EA pads with 2 mm, 3 mm, and 4 mm electrode spacing is 0.45 N, 0.46 N, and 0.48 N, respectively. Furthermore, 0.07 N, 0.09 N, and 0.10 N are the maximum normal forces produced by EA pads with 2 mm, 3 mm, and 4 mm electrode spacing, respectively. As a result, the 4 mm electrode spacing was chosen for the EA pad design in order to maximize safety and EA force and provide the best results.Tangential EA forces of EA pads with various dielectric layer thicknesses were investigated since the thickness of the dielectric layer can impact the output of the EA force. Four EA pads with dielectric layer thicknesses of 0.4 mm, 0.6 mm, 0.8 mm and 1 mm were constructed accordingly. Five tangential force tests were done for each EA pad using the tangential force measuring instrument. It can be seen in The VSEAF was placed horizontally on a PLA frame, as illustrated in x-axis of the low-melting-point alloy . The reciprocal of stiffness and flexibility shows that the stiffness and flexibility have an inverse relationship with the slope of the curve. Studying the bending performance of the VSEAF is very significant since the bending performance of soft fingers is a key indicator for revealing the workspace of a soft pneumatic gripper. The measurement and comparison of the bending angle corresponding to different inflation pressures are shown in The EA function allows the VSEAF to safely grasp both convex and flat objects, unlike other pneumatic grippers. The ability of the VSEAF to grip a square piece of paper with dimensions of 120 mm × 120 mm and a weight of 1.2 g is shown in In As illustrated in Five tests were conducted for the VSEAF soft state and stiff state under various inflation pressures. We proposed a pneumatic gripper by integrating a variable stiffness EA pad. The proposed gripper combines the benefits of electroadhesion and soft pneumatic grippers, as well as the capability of changing stiffness. This gripper can grab both flat and convex objects, and its stiffness may be adjusted to boost the gripping stability.This study presents a simple and lightweight pneumatic electro-adhesive gripper with variable stiffness. The primary contributions of this study are (1) the creation of the idea of a variable stiffness pneumatic electroadhesive gripper, (2) the variable stiffness EA gripper manufacturing process, and (3) the development of a three-fingered VSEAF gripper.Due to the temperature regulation of the VSEAF, the VSEAF in this research cannot grab high-temperature objects (above 47 °C), necessitating the need for an insulator in future designs. Additionally, future research will involve modeling and optimizing the VSEAF’s structure for enhanced performance, such as a greater EA force, using modeling and simulation.


Passive ankle joint stiffness was normalized by the body mass. There was no correlation between the absolute ankle joint stiffness and muscle shear modulus of triceps surae in the young and older groups at the NP . Significant positive correlations between absolute ankle joint stiffness and muscle shear modulus at DF15 were observed for MG and Sol in the young group  but not in the older group. The normalized ankle joint stiffness at the NP was significantly positively correlated with the LG shear modulus in young participants and with the MG and LG shear modulus in older participants (r ≥ 0.466 and p ≤ 0.039). There were significant positive correlations between the normalized ankle joint stiffness and the muscle shear modulus of the triceps surae at DF15 in young and older participants (r ≥ 0.464 and p ≤ 0.040), except for the MG shear modulus in older participants (r = 0.419 and p = 0.066). These results suggest that the material properties of the entire triceps surae, even Sol, which is the most compliant muscle among the triceps surae, affect passive ankle joint stiffness, especially when the triceps surae is lengthened and body size is considered.This study aimed to investigate whether triceps surae muscle stiffness is associated with passive ankle joint stiffness in 40 young (21–24 years) and older (62–83 years) males. Using ultrasound shear wave elastography, the shear modulus of each muscle of the triceps surae  was assessed as muscle stiffness at the ankle neutral position (NP) and 15-degree dorsiflexed position (DF15) with the knee fully extended. Passive ankle joint stiffness at the NP and DF15 was calculated as the gradient of the angle–torque relationship at each joint angle during passive ankle dorsiflexion at 1°∙s Joint flexibility is a vital physical fitness factor for most individuals. For instance, high joint flexibility contributes to better athletic performance, such as in gymnastics  and figu−1) can be calculated by dividing the joint torque (Nm) by the change in the joint angle (degree). Muscle stiffness is considered one of the major influential factors for both indices of joint flexibility . Recently, muscle stiffness has been indirectly estimated using ultrasound shear wave elastography (SWE) in many studies  stiffer triceps surae would be associated with higher passive ankle joint stiffness regardless of the age group and 2) the association of triceps surae stiffness with passive ankle joint stiffness would be stronger in the ankle dorsiflexed position than in the ankle neutral position (NP).To compute the required sample size for a correlation analysis in each young and older adult, a priori power analysis was conducted using the G*Power statistical power analysis software . A type 1 error and a statistical power were set at 0.05 and 0.80, respectively. The effect size was assumed to be 0.60 according to a previous study . The cri−1 between 30 degree of plantar flexion (PF30) and 15-degree dorsiflexion (DF15) (NP was defined as 0°) to familiarize the participants with the passive dorsiflexion motion by the dynamometer and to avoid a conditioning effect on tissue stiffness  activity of the triceps surae to ascertain muscular relaxation. Immediately after the passive ankle dorsiflexion task, the ankle was returned to the plantar flexed position to avoid a stretching effect on muscle stiffness. Subsequently, a muscle stiffness assessment was conducted for each triceps surae muscle using an ultrasonic SWE . The muscle stiffness assessment was randomized and counterbalanced among the participants. For each muscle, muscle stiffness was assessed firstly at the NP and secondly at DF15 with no rest period. Following the completion of this sequential assessment, a 2-min rest period was provided, with the ankle plantar flexed position. Then, the next muscle stiffness assessment was performed. This measurement-rest cycle was repeated until the finishing muscle stiffness assessment for the entire triceps surae was completed. Finally, maximal voluntary isometric contraction (MVIC) of the plantar flexors was performed for 3 s in the NP to normalize the EMG activity. The ankle joint angle, passive joint torque, and the EMG data were simultaneously stored at 1 kHz on a personal computer through a 16-bit analog-to-digital converter .Participants lay prone on a dynamometer bed . Their hips and knees were fully extended. After a visual check to align the rotational axes of the right ankle and dynamometer, the right foot was fixed to the foot plate of the dynamometer with non-elastic straps. Before the actual measurement, five repetitions of passive ankle dorsiflexion and plantar flexion were performed at 5°stiffness . To evalIn this study, the muscle shear modulus, which was evaluated by SWE using an ultrasonographic device  coupled with a linear transducer array , was used as an index of the muscle stiffness . AccordiTo ascertain muscular relaxation during passive ankle dorsiflexion motion (joint stiffness measurement) and muscle shear modulus measurement, the EMG activity was recorded from the MG, LG, and Sol. Prior to electrode attachment, the skin was prepared . Pre-amplified surface EMG electrodes  with band-pass filtering between 20 and 450 Hz  were then placed. The electrodes were located just beside the muscle shear modulus measurement location for the MG and LG, and midway between the distal myotendinous junction of the LG and Sol for Sol. The reference electrode was attached to the left medial malleolus.4 + bx3 + cx2 + dx + e, where y is the torque, x is the ankle joint angle , and a–e are constants) according to previous studies . The passive ankle joint stiffness (slope of the passive torque-joint angle curve) was calculated at NP and DF15 using the first derivative of the equation . The passive ankle joint stiffness was normalized by the body mass.The passive ankle joint stiffness was evaluated using a fourth-order polynomial equation fitted to the passive torque-joint angle curve for each participant   . The meaFor the EMG data, the root mean square (EMG-RMS) value for each muscle was calculated over the entire period of passive ankle dorsiflexion motion (passive joint stiffness measurement) and a 500-ms period at NP and DF15 during the muscle stiffness measurements. The EMG-RMS values were normalized to the EMG-RMS values for 500 ms during MVIC.t-test was performed to compare the physical characteristics, passive ankle joint stiffness, and muscle shear modulus between young and older participants. As the EMG activity was not normally distributed, the Mann–Whitney U test was conducted to compare young and older participants. A Pearson product-moment correlation analysis was conducted to investigate the association between the absolute and normalized ankle joint stiffness and the muscle shear modulus. The significance level was set at α = 0.05. Data are presented as mean ± standard deviation unless otherwise indicated. A 95% confidence interval for the difference or correlation coefficient was reported. Effect sizes were also reported as follows: Cohen’s d for the independent t-test, r for the Mann–Whitney U test, and r for correlation analysis. We considered the effect sizes for the independent t-test d ≥ 0.8 as large effects, ≥ 0.5 as medium effects, and ≥ 0.2 as small effects; effect sizes for the Mann–Whitney U test r ≥ 0.5 as large effects, ≥ 0.3 as medium effects, and ≥ 0.1 as small effects; and effect sizes for correlation analysis r ≥ 0.5 as large effects, ≥ 0.3 as medium effects, and ≥ 0.1 as small effects . Muscle shear modulus of the triceps surae in the young group was significantly higher at the NP than that in the older group, with moderate effects . For the muscle shear modulus of the triceps surae at DF15, no significant difference was observed between young and older participants . p ≤ 0.046, r ≥ 0.448), and MG and LG during the muscle stiffness measurement with large effects .r ≤ 0.349 and p ≥ 0.138, LG: r ≤ 0.284 and p ≥ 0.236, Sol: r ≤ 0.195 and p ≥ 0.416). The absolute joint stiffness at DF15 was significantly positively correlated with the MG and Sol shear modulus with moderate to large effects but not the LG shear modulus in young participants . There were no significant correlations in older participants .r = 0.424 and p = 0.061, LG: r = 0.466 and p = 0.039, Sol: r = 0.280 and p = 0.219), and the MG and LG shear modulus with moderate to large effects in the older participants . There were significant positive correlations between the normalized joint stiffness and the muscle shear modulus of the triceps surae at DF15 with moderate to large effects in young participants . Moreover, there were significant positive correlations with moderate to large effects in older participants, except for the MG shear modulus . The main findings of our study were as follows: 1) Absolute ankle joint stiffness at the NP was not associated with any of the muscle shear moduli of the triceps surae in the young and older groups. 2) Absolute ankle joint stiffness at DF15 was associated with the muscle shear modulus in young participants, but not in older participants. 3) Normalized ankle joint stiffness at the NP was associated with muscle shear modulus of the gastrocnemii but not the Sol shear modulus in both groups. 4) Normalized ankle joint stiffness at DF15 was associated with the muscle shear modulus of almost all triceps surae in both the groups. These results partially support our hypothesis. These findings suggest that stiffness of the entire triceps surae, even Sol, which is the most compliant muscle between the triceps surae, affects passive ankle joint stiffness, especially when the triceps surae are lengthened and normalized to body mass.−1), of these muscles is different. Considering that absolute joint stiffness (Nm∙degree−1) is a size-dependent measure with individual differences in the body size, it is not surprising that the muscle shear modulus of the triceps surae rarely correlates with the absolute ankle joint stiffness. In addition, the muscle shear modulus develops exponentially with passive muscle stretching . Considering these results, the normalized ankle joint stiffness would be more easily associated with the muscle shear modulus than absolute stiffness. Therefore, it is reasonable that the material properties of the triceps surae are associated with the normalized ankle joint stiffness. However, at the NP, the Sol shear modulus did not correlate with the normalized ankle joint stiffness in either group. The Sol is known to be the most compliant muscle in the triceps surae , influential factors are not only the plantar flexors, including the triceps surae, but also the dorsiflexors. For instance, in the ankle dorsiflexion position , the plantar flexors are stretched and generate high passive tension, whereas the dorsiflexors are slack . Hence, The absolute and normalized ankle joint stiffness did not vary between young and older participants, regardless of the ankle joint angle . In lineJoint flexibility is regarded important in numerous aspects such as athletic performance , sports-This study had several limitations. First, the muscle stiffness was evaluated as the muscle shear modulus using an ultrasound SWE. Although SWE has been widely used to estimate tissue stiffness in recent years, this estimation is based on many assumptions, such as tissue density and linear elastic behavior. In contrast, the validity and usefulness of SWE for muscle stiffness assessments have been reported . We beliThe purpose of this study was to investigate the association between the triceps surae muscle and passive ankle joint stiffness. The results revealed that the muscle shear modulus of the entire triceps surae influences the passive ankle joint stiffness, especially when the triceps surae/ankle joint is lengthened/dorsiflexed and the ankle joint stiffness is normalized to body size. Additionally, even Sol, which is the most compliant muscle between the triceps surae, affects the passive ankle joint stiffness. Moreover, the results also indicate that the association between the muscle shear modulus and ankle joint stiffness is independent of age, although the association is clearer in young than in older adults due to age-related decrease in the contribution of muscle stiffness to joint stiffness. These findings suggest that modulation of the triceps surae stiffness may change the ankle joint stiffness, leading to the improvement of functional ability, such as postural balance and walking, and decrease in injury and fall risks.


Enterobacter cloacae is mainly responsible for sepsis, urethritis, and respiratory tract infections. These bacteria may affect the transcription of the host and particularly their immune system by producing changes in their epigenetics. In the present study, four proteins of Enterobacter cloacae were used to predict the epitopes for the construction of an mRNA vaccine against Enterobacter cloacae infections. In order to generate cellular and humoral responses, various immunoinformatic-based approaches were used for developing the vaccine. The molecular docking analysis was performed for predicting the interaction among the chosen epitopes and corresponding MHC alleles. The vaccine was developed by combining epitopes , which include the adjuvant Toll-like receptor-4 (TLR4). The constructed vaccine was analyzed and predicted to cover 99.2% of the global population. Additionally, in silico immunological modeling of the vaccination was also carried out. When it enters the cytoplasm of the human (host), the codon is optimized to generate the translated mRNA efficiently. Moreover, the peptide structures were analyzed and docked with TLR-3 and TLR-4. A dynamic simulation predicted the stability of the binding complex. The assumed construct was considered to be a potential candidate for a vaccine against Enterobacter cloacae infections. Hence, the proposed construct is suitable for in vitro analyses to validate its effectiveness. Enterobacter cloacae. Enterobacter spp. the second most prevalent carbapenem-resistant Enterobacteriaceae (CRE) in the United States, has an increasing role in the spread of carbapenem-resistant infections [Enterobacter cloacae are anaerobic Gram-negative bacteria involved in neonatal infections that are associated with morbidity and multi-drug resistant infections [Respiratory tract and urinary tract infections are mostly caused by the pathogen fections . Enterobfections . It has fections . New evifections .E. cloacae to amoxicillin, ampicillin, cefoxitin and cephalosporins, regardless of AmpC-lactamase production [There is intrinsic resistance of oduction . There ioduction ,5. Becauoduction . Fourth-oduction .E. cloacae [Microorganisms possess key regulators known as epigenetics, which work as protective mechanisms by altering gene activity without modifying the DNA sequence . Many in cloacae ,11. Trea cloacae ,9.E. cloacae that play a role in the epigenome of the host. The vaccine construct was developed using an in silico technique. The cytotoxic T-lymphocyte (CTL), B-cell, and also HT-lymphocyte (HTL) epitopes were obtained by performing computational analysis on the chosen protein sequences. The allergenicity, antigenicity, and toxicity of specific epitopes was accessed. The selected epitopes were also evaluated to check whether they have the ability to develop autoimmunity or not. The docking analysis was performed among epitopes and their corresponding MHC alleles to calculate the vaccine construct population coverage worldwide. Furthermore, this study predicts the validation of the hypothesis by performing an in silico immune simulation. The hierarchical approach for the 3D structure prediction was performed for the peptide sequence of the vaccine design and was docked against TLR-3 and TLR-4. Finally, the stability of the vaccine complex was validated using molecular dynamic modeling.The primary objective of the current study was to create a new multi-epitope mRNA vaccine employing outer membrane porins (OMPs) of http://www.uniprot.org, accessed on 25 November 2021). The bacterial sequences in amino acid form were retrieved through the Uniport database in FASTA format of protein OmpF (Accession Id-V5ISF4), OmpD (Accession Id-A0A2T4Y430), OmpC (Accession Id-Q93K99), and Omp35 (Accession Id-G3LW48). The sequences retrieved were subjected to highly immunogenic spot for the prediction of efficient epitopes [The sequence of amino acids of bacterial proteins that are involved in porin activity and ions transmembrane transport were obtained from the database Uniport  analysis was performed to predict the immunogenicity or antigenicity of retrieved bacterial protein sequences. The algorithm of Auto Cross Covariance (ACC) was selected to predict the results with an accuracy level up to 89%. The server Aller-TOP  was employed to predict allergenicity of retrieved bacterial protein sequences.The VaxiJen . To execute, the server needed FASTA sequences of chosen proteins. To predict the epitopes, 9 and 10 mer lengths were selected and artificial neural networks (ANN) method was used. For the ultimate prediction results of the epitopes, human complete set HLA was used and sorted by IC50 assessment. The epitopes over 500 IC50 values were selected for further interpretation [The outer membrane protein sequences were analyzed for the screening of CLT epitopes by computational tools of the MHC-I IEDB server  was utilized to predict B-cell epitopes. The artificial machine learning approach was performed for epitope prediction. A 0.5 threshold was used to submit each protein sequence. The selected epitope’s length was 16 mer. Moreover, the overlap filter remained active. The top epitope results were chosen for further investigation.The webserver of ABCpred (http://tools.iedb.org/mhcii/ accessed on 27 November 2021) was run to obtain information on HTL epitopes in relation to a comprehensive human HLA reference set [http://crdd.osdd.net/raghava/ifnepitope/predict.php accessed on 27 November 2021), IL-10 pred (https://webs.iiitd.edu.in/raghava/il10pred/predict3.php accessed on 27 November 2021) and IL-4 pred (https://webs.iiitd.edu.in/raghava/il4pred/predict.php accessed on 27 November 2021) online tools were used to predict that the selected epitopes secrete IFN-γ, IL-10 and IL-4, which particularly stimulate interferon–gamma cytokines. This server’s algorithm utilized a hybrid technique that combines the strengths of the motif and SVM models [An IEDB database MHC-II server (ence set . The proence set . The epience set . The IFNM models .https://blast.ncbi.nlm.nih.gov/Blast.cgi?PAGE=Proteins accessed on 28 November 2021). If the E-value was more than 0.05, all peptides in the vaccine were considered possible non-homologous peptides.All predicted peptides were compared to Homo sapiens (TaxID: 9606) protein database performing the BLASTp tool (http://www.ddg-pharmfac.net/Vaxijen/VaxiJen/VaxiJen.html accessed on 1 December 2021) was employed [http://www.ddg-pharmfac.net/AllerTOP accessed on 1 December 2021) was employed. All factors were set to their default values [https://webs.iiitd.edu.in/raghava/toxinpred/multisubmit.php accessed on 1 December 2021) server for toxicity analysis was used to determine and measure the toxicity of the epitopes. Only the antigenic, non-toxic, and non-allergenic epitopes were chosen for additional analysis [All particular epitopes were evaluated for antigenicity, allergenicity, and toxicity . To evalemployed . The preThe database of NCBI was utilized to obtain all potential variations of specified proteins. The Bio-Edit sequence alignment tool was run for multiple alignment sequence, alignments, and visualization. The conserved areas found epitopes and then further screened them out and used for next interpretation.https://cluspro.bu.edu/login.php accessed on 3 December 2021) was utilized for computing binding affinity and to dock each epitope along its associated MHC allele. PyMOL or Discovery Studio were used to assess the orientation and interactions.The molecular docking modeling used for the interpretation of binding affinity of retrieved T-lymphocytes with the MHC alleles. The MHC alleles’ 3D structures were obtained from the PDB-Database. After that, the structures were optimized with the PyMOL tool to remove the unnecessary ligands. Following that, ClusPro (http://tools.iedb.org/population/ accessed on 4 December 2021) was used to compute coverage for vaccine design to target T-lymphocyte epitopes and associated MHCI and MHCII alleles [The IEDB database’s Coverage of Population webserver -EAAAK Linker- Resuscitation-promoting factor (RpfE) (Adjuvant)-GPGPG linker-HTL Epitopes-KK-B-Cell Epitopes-AAY Linker-CTL Epitopes—MITD sequence-Stop codon-3′ UTR-Poly (A) tail.Three linkers were used to connect all predicted epitopes: GPGPG, KK, and AAY. These linkers exist to divide domains and to allow them to function independently. They can be cleaved, are flexible, and are hard. To increase the adaptive immune response, an adjuvant RpfE was used. A Kozak sequence, which includes a start codon in the ORF and a stop codon, must be included in the mRNA vaccine. In addition, the construct was given two structures: first, the tissue Plasminogen Activator (tPA) secretory signal sequence (UniProt ID: P00750) in the construct’s 5′ region. This is a signal sequence that aids in the secretion of epitopes once they have been translated from cells; second, the MHC I-targeting domain (MITD) (UniProt ID: Q8WV92) in the 3′ locus end of the mRNA vaccine. http://scratch.Proteomics.ics.uci.edu/ accessed on 6 December 2021) is established on data obtained through the analysis of microarray and machine learning algorithms. The input of mRNA vaccines consists of only the amino acid sequence, with no tPA or MITD sequences.The VaxiJen and ANTIGENpro servers were run for the evaluation of antigenicity of the design. This interpretation was important because antigenicity of an epitope may induce an immunity and memory to generate cell production . VaxiJenhttps://web.expasy.org/protparam/ accessed on 7 December 2021) was used. Among these characteristics are the amino acid concentration, theoretical isoelectric point (pI), molecular weight, Aliphatic Index (AI), Instability Index (II), and Grand Average of Hydropathicity (GRAVY) [The AllerTOP 2.0 server was used for evaluation of the construct’s allergenicity and to ensure that there are not any allergenic factors, and the ToxinPred server was used to assess the vaccine’s toxicity. Finally, to estimate the vaccine’s various physicochemical parameters, ProtParam webserver ( (GRAVY) .http://150.146.2.1/C-IMMSIM/index.php accessed on 9 December 2021) was used to evaluate immunological response of the vaccine design while leaving the parameters at default. The mechanism based on the interaction of epitopes with receptors of the lymphocyte impersonated the immunological response. Most contemporary vaccines prescribe two to three doses every four weeks. As a result, in this study’s immunological simulation, three doses of 1000 vaccine units were administered during a four-week period. Three injections were run at distinct time-steps of 1, 84, or 168.The server of the C-ImmSim simulation (http://www.genscript.com/ accessed on 10 December 2021) was used. The optimized sequence’s quality was evaluated using GenScript’s Rare Codon Analysis tools. The Codon Adaptation Index indicates the efficiency of mRNA translation (CAI). Codon Frequency Distribution indicated the presence of any tandem uncommon codons (CFD).For effective production within human cells, the peptide vaccine construct must be codon optimized. As a result, GenScript’s (GSs) tool of GenSmart Codon Optimization (http://rna.tbi.univie.ac.at/cgi-bin/RNAWebSuite/RNAfold.cgi accessed on 11 December 2021) was used to predict the secondary structure of the mRNA vaccine. It leverages McCaskill’s method to calculate the lowest free energy of the expected secondary structure (MFE). The minimal free energy (MFE) of the structure and the centroid secondary structure, as well as their minimum free energy, were calculated [The RNAfold tool (lculated .http://bioinf.cs.ucl.ac.uk/psipred/ accessed on 13 December 2021) was utilized to predict the peptide’s secondary structure using position-specific scoring matrices with an accuracy of 84.2 percent [https://robetta.bakerlab.org/ accessed on 14 December 2021). To confirm the optimum structure, ProSA-web (https://prosa.services.came.sbg.ac.at/prosa.php accessed on 14 December 2021), ERRAT (https://saves.mbi.ucla.edu/ accessed on 14 December 2021), and PROCHECK were performed.The PSIPRED tool ( percent . A peptihttp://tools.iedb.org/ellipro/ accessed on 16 December 2021), was used to estimate the protein structure’s discontinuous B-cell epitopes [The protein’s tertiary structure can elicit novel conformational B-cell epitopes . ElliProepitopes . Elliprohttps://haddock.science.uu.nl/ accessed on 17 December 2021) was used to calculate the free dissociation constant (Kd), binding energy (G), and percentages (%) of polar and charged amino acids on the non-interacting surface by receptor–ligand 3D interaction [The vaccine peptide and Toll-like receptor 4 (TLR-4) (PDB ID: 3FXI) or TLR-3 (PDB ID: XI) (PDB ID: 1ZIW) were used for docking. The PIPER docking technique was used to dock 3D buildings on the ClusPro server. A RpfE adjuvant was docked against TLR4 and TLR3 as a control. This server may generate many models based on different scoring methods. The PRODIGYY tool on the HADDOCK website (eraction . http://imods.chaconlab.org/ accessed on 20 December 2021) executed dynamics simulation analysis for the TLR4-vaccine and TLR3-vaccine complex structures with the lowest binding energy to verify the mobility and stability of the vaccine’s complex structures and molecules.The iMODS server  shows epitopes of HTL, and the lymphocyte can secrete the chemokines that perform critical functions against these bacteria. Excluding memory cells, all immune cells die after infection is eradicated. The membrane-bound immunoglobin receptor of B-cells is used to recognize the antigenic epitopes. Consequently, it induces the epitopes and processes them before presenting them against T-cells through MHC class-II molecules. These are recognized by T-cell receptors (TCR). As a result, plasma cells differentiate from B-cells and secrete antibodies by neutralizing memory and intruder cells.Enterobacter cloacae proteins. These proteins affect the outer membrane of the host organisms. The target proteins are examined for epitopes, which might induce responses of humoral or cell mediation. The web-based IEDB database that predicts epitopes of HTL and CTL are based on immune epitope determination. ABCpred, an internet service, was used to anticipate B-cell epitopes. This server used an artificial machine learning method to predict the epitopes. The evaluation of epitopes was assessed by determining antigenicity, allergenicity and toxicity by using web servers. Specific linkers were used to combine the epitopes together. To boost immunity, the TLR4 immune receptor was added at the N-terminus of the construct. Moreover, an immune simulation of vaccine effects was carried out to validate the humoral and cellular responses of the vaccine. To combat infection crises, we developed an in silico based multi-epitope mRNA vaccine based on The vaccine construct’s targeted epitopes have 92 corresponding MHC alleles. The five chosen epitopes were further exposed for molecular docking. Since the interaction of ligands and epitopes is essential in vaccine design, docking analysis was performed among the chosen epitopes and their corresponding MHC alleles. The ClusPro predicts binding affinity and bond formation of the chosen epitopes. When the energy values are lowest, the receptor strongly binds to the ligands. The interactions among the epitopes and MHC pockets were also analyzed. Furthermore, because there are over one thousand different human MHC alleles, vaccination is only effective in those who have a certain MHC allele that binds the epitope. As a result, the tool of IEDB population coverage predicted that the vaccination would cover 99.2% of the world’s population.Several types of structures were used to improve stability and translation in the mRNA-based construct. These are the 5′ m7G cap sequences, Globin 5′ and 3′ UTRs bordering the mRNA ORF, Poly (A) tails varying in length from 120 to 150 bps, the Kozak sequence, and the stop codon. In addition, to boost the construct’s efficacy and allocation, the MITD sequence and the tPA secretory signal sequence were inserted to drive it into the endoplasmic reticulum ,34. Furthermore, the TLR-3 and TLR-4 immune receptors had been docked with the vaccine construct to evaluate the vaccination’s capacity to bind to or to interact by immune receptors. According to the findings, the vaccine has a strong affinity for binding to TLR-4 and TLR-3. As a result, there is a possibility of developing innate and adaptive immunity. The complex’s stability was investigated using molecular dynamic simulation. The mRNA vaccine may be utilized when deprived of an adjuvant. This method has both advantages and disadvantages. By revealing the sequence to annihilation in a wet-lab study, it may save time and money. As a result, an applied study is required to determine which step is necessary.Enterobacter infections.The recommended mRNA vaccine’s peptide sequence was demonstrated to be stable, thermostable, antigenic, non-allergenic, as well hydrophilic using immunoinformatics approaches. Once delivered in silico with three injections, it was able to elicit an immunological response . It was Enterobacter cloacae, with multiple serological analyses used to validate the trigger of response in demand.The vaccine construct shows appropriate physiochemical and immunological responses. The immunological simulation demonstrated that the vaccination induced an immunity response that was reliable with our objectives. Hence, it is advised that this construct is used as a prospective applicant for in vitro and in vivo studies in contraindications to


The increasing organ shortage in kidney transplantation leads to the necessity to use kidneys previously considered unsuitable for transplantation. Numerous studies illustrate the need for a better decision guidance rather than only the classification into kidneys from standard or expanded criteria donors referred to as SCD/ECD-classification. The kidney donor profile index (KDPI) exhibits a score utilizing a much higher number of donor characteristics. Moreover, graft biopsies provide an opportunity to assess organ quality.In a single center analysis 383 kidney transplantations (277 after deceased and 106 after living donation) performed between January 1st, 2006, and December 31st, 2016, retrospectively underwent SCD/ECD and KDPI scoring. Thereby, the quality of deceased donor kidneys was assessed by using the KDPI and the living donor kidneys by using the living KDPI, in the further analysis merged as (L)KDPI. Baseline biopsies taken 10 min after the onset of reperfusion were reviewed for chronic and acute lesions. Survival analyses were performed using Kaplan-Meier analysis and Cox proportional hazards analysis within a 5-year follow-up.r = 0.30, p < 0.001), arteriosclerosis , interstitial fibrosis, and tubular atrophy  as well as the extent of acute tubular injury . The C-statistic of the (L)KDPI concerning 5-year death censored graft survival was 0.692. Around 48% of ECD-kidneys were classified as (L)KDPI<85%. In a multivariate Cox proportional hazard analysis including (preformed) panel reactive antibodies, cold ischemia time, (L)KDPI, and SCD/ECD-classification, the (L)KDPI was significantly associated with risk of graft loss (hazard ratio per 10% increase in (L)KDPI: 1.185, 95% confidence interval: 1.033–1.360, p = 0.025). Survival analysis revealed decreased death censored (p < 0.001) and non-death censored (p < 0.001) graft survival in kidneys with an increasing (L)KDPI divided into groups of <35, 35–85, and >85%, respectively.The (L)KDPI correlated with glomerulosclerosis (With a higher granularity compared to the SCD/ECD-classification the (L)KDPI is a promising tool to judge graft quality. The correlation with chronic and acute histological lesions in post-reperfusion kidney biopsies underlines the descriptive value of the (L)KDPI. However, its prognostic value is limited and underlines the urgent need for a more precise prognostic tool adopted to European kidney transplant conditions. There is a worldwide shortage of organs suitable for kidney transplantation and especially in Germany the demand clearly exceeds the allocable organ numbers , 2. TherThe distinction between standard criteria donors (SCD) and ECD was introduced to grade graft quality, identifying 4 simple characteristics  . ECDs arThe KDPI (kidney donor profile index) is an index displayed as a cumulative percentage scale representing the risk for kidney transplant failure. For example, the graft of a donor with a KDPI of 70% has a higher predictive risk of graft failure than 70% of the grafts transplanted in the precedent year , 11. TheIncreasing donor age is not limited to cadaveric kidneys but also affects kidneys from living donors. Furthermore, donor age is a predictor of graft function in kidney transplantation after living donation . The livHere we investigated on the additional prognostic value of the (L)KDPI in SCD and ECD kidneys from a single center cohort by use of routinely taken baseline-biopsies 10 min after the onset of reperfusion. This allows for the consideration of histological graft quality including tubular injury following transplantation in the evaluation of the (L)KDPI as prognosis score in renal allografts from SCD and ECD.All kidney transplantations with baseline biopsy during transplant surgery after deceased or living donation at Klinikum rechts der Isar, Munich, Germany between January 1st, 2006, and December 31st, 2016, were included in this retrospective analysis. These baseline biopsies were taken routinely 10 min after the onset of graft reperfusion by core needle (18G) biopsy as part of the clinic's internal standard of care protocol to allow for initial assessment of graft quality by baseline histology.All patients included into this study were at least 18 years old at time of transplantation. Informed consent was obtained for using the kidney specimens retrospectively for further investigation. The local ethics committee of the Technical University of Munich, Germany had approved this retrospective analysis of the cohort (No. 178/21s). For data collection the hospital's information system, patient records, routine clinical follow-up from external nephrologists, and the Eurotransplant Network Information System (ENIS) for donor and recipient data were used. Patients were followed up until June 30th, 2017 (data lock).Recipients with early graft failure due to perioperative  complications were excluded from further statistical analyses.Recipients were subclassified whether they received an organ from SCDs or ECDs according to the definition by Port et al. as written above .For the calculation of the KDRI, ten donor characteristics  were used as guided by the Organ Procurement and Transplantation Network (OPTN) . In caseThe LKDPI was calculated by using donor and recipient factors such as age, eGFR, BMI, ethnicity, history of cigarette use, systolic blood pressure, sex, AB0 incompatible transplantation, relation, HLA status, and donor/recipient weight ratio .Both KDPI and LKDPI were divided in groups , inspired by the OPTN. Delayed graft function (DGF) was defined as proposed by the OPTN: need for dialysis during the first week after transplantation .The primary endpoint was death censored transplant failure, comprising permanent need for dialysis after transplantation, including both primary non-function  and follow-up end-stage transplant failure requiring reinstitution of dialysis. In the event of death with a functioning graft, the follow-up period was censored at date of death . Graft fPrimary non-function was defined as an initially non-working allograft with need for intermittent dialysis after transplantation, without accountable perioperative complications, and with proven organ perfusion confirmed by ultrasound examination.The secondary endpoint was non-death censored transplant failure, which is a composite of primary non-function, follow-up end-stage transplant failure requiring the reinstitution of dialysis, and recipient death with a functioning allograft. Furthermore, we hypothesized that the (L)KDPI is associated with factors representing limited organ quality and prolonged transport, ECD, increased cold ischemia time, and histological findings in the baseline biopsy such as the histological extent of (acute) tubular injury (ATI), interstitial fibrosis and tubular atrophy (IF/TA), arteriosclerosis and glomerulosclerosis.All biopsy specimens included in this study were retrospectively reviewed by the same experienced renal pathologist (M.B.-H.), who was blinded for clinical data. The biopsy specimens were core-needle biopsies prepared on slides containing paraffin sections (2–4 μm) that were stained with hematoxylin and eosin (HE) and periodic acid–Schiff (PAS).Chronic lesions in the biopsies were assessed. The severity of arteriosclerosis was scored semi-quantitatively according to revised Banff Classification. The severity of IF/TA was reported as a percentage concerning the proportion of the affected cortical area in the biopsy sample. Glomerulosclerosis was expressed as a percentage of the total number of glomeruli in the biopsy .ATI was scored as previously described  and the t-test for normally distributed data and chi-square (χ2) tests for categorical data. Pearson's correlation was used to assess associations between metric, normally distributed data, Spearman rank correlation between metric and ordinal, Eta coefficient (η) between metric and nominal data, and the χ2 -test (ϕ) between ordinal and nominal scaled variables.Normally distributed data was summarized by mean ± standard deviation, for skewed data median and interquartile range (IQR), represented as first quartile to third quartile, are shown. Categorical data is displayed as absolute number (n) and percentage of the total number (%). Comparisons between groups of the baseline characteristics was performed by using Kruskal-Wallis and Mann-Whitney U test for non-normally distributed data, univariate ANOVA and Kaplan-Meier analysis, univariate and multivariate Cox proportional-hazards analysis, and log-rank tests were used to examine the association between the SCD/ECD-classification as well as the (L)KDPI and the primary and secondary endpoint. Univariate and multivariate Cox proportional-hazards analyses were calculated with the 5-year follow-up values.For estimation of hazard ratios, Cox proportional-hazards models were fitted to the data. Those multivariate models included recipient and donor associated risk factors from univariate analysis for the primary endpoint (death censored transplant failure). The (L)KDPI score was included in a Cox proportional-hazards analysis as a continuous variable. All tests were performed two-sided using a significance level of α = 0.05. C-statistics  were estStatistical elaboration was performed using the software programs “IBM SPSS Statistics” version 25  and “R” version 3.4.4 . In addition, GraphPad Prism, version 7.0 (Graph-Pad Software) was used for data presentation.In total, 406 potential kidney transplantations  which unOf these 383 remaining transplantations, 277 underwent KDPI scoring according to deceased donation and 106 transplantations underwent LKDPI scoring after living donation. During the observation period five patients were transplanted twice due to early failure of first kidney transplant. Further, of the 277 deceased donations 150 (54%) were classified as SCD and 127 (46%) as ECD. In living donations 73 (69%) were classified as SCD and 33 (31%) as ECD. Detailed baseline demographics are presented in Since in Germany non-heart-beating kidney donation is not possible all deceased donations in this cohort were donations after brainstem death (DBD) and will be referred to as such.Of 383 initially taken biopsy samples, 54 specimens were not available for further analysis due to poor specimen quality, e.g., insufficient cortical tissue or autolysis. The median follow-up time for recipients at the time of data extraction from the clinical follow-up database  was 4.8 (0.1–11.4) years. During observation, three patients were lost to follow-up and censored: one patient after deceased donation after 54 days and two patients after living donation (after 342 and 428 days).p = 0.018). Of these, only one patient received a living donation (LKDPI 35–85%). There also were significant differences in the eGFR of renal grafts 3 years after transplantation in the three categories (L)KDPI <35, 35–85, and >85% with eGFRs of 61 ml/min/1.73 m2, 45 ml/min/1.73 m2, and 39 ml/min/1.73 m2 (p < 0.001), respectively. Focusing on transplantation after deceased donation only, the eGFR after 3 years showed comparable values in the three (L)KDPI categories: 65 ml/min/1.73 m2, 45 ml/min/1.73 m2, and 38 ml/min/1.73 m2 (p < 0.001). No significant differences were present in the number of rejections 1 year after transplantation between the (L)KDPI groups, neither for all transplantations nor within the recipients after deceased donation. Average dialysis vintage was not different between the 3 KDPI-groups of kidney transplantations after DBD. Significant differences were also present in 3 year-eGFR and PNF for transplants divided by the SCD/ECD-criteria, whereas there was no significant difference for biopsy proven rejections (BPRs) as shown in Within 5 years after transplantation 47 patients suffered from transplant failure and 34 patients died with a functioning allograft. Of these, 8 patients with transplant failure had a transplant with a KDPI or LKDPI [(L)KDPI] of <35%, 17 patients of 35–85%, and 22 patients of more than 85%. Primary non-function occurred in 1 kidney transplant with a (L)KDPI of <35%, in 6 transplants of 35–85% and in 7 transplants of more than 85% (p < 0.001). Nonetheless, average death censored graft survival in the high-risk group was still 7.5 years (±1.2 years). Mean death censored graft survival time was 9.3 years (±0.7 years) in the medium- and 10.3 years (±1.2 years) in the low-risk group. In transplantation from DBDs it was 9.1 (±0.8 years) and 10.6 years (±0.6 years), respectively. The median LKDPI in transplantations after living donation was 28  whereas the median KDPI after deceased donation was 67  transplanted kidneys with (L)KDPI of <35%, in 66/171 (39%) transplanted kidneys with (L)KDPI of 35–85%, and in 34/85 (40%) transplanted kidneys with (L)KDPI of >85% (p < 0.001). The recipient's Charlson Comorbidity Index correlated with the (L)KDPI of all recipients irrespective of living or deceased donation .Transplant failure and death with functioning graft increased significantly with a (L)KDPI >85% compared to (L)KDPI <35% and 35–85% . Graft lp < 0.001) and non-death censored graft survival (HR per 10% increase in (L)KDPI: 1.221, 95% CI: 1.129–1.231, p < 0.001). Likewise, this was applicable to the KDPI after deceased donation for death censored graft survival (HR per 10% increase in (L)KDPI: 1.297, 95% CI: 1.153–1.459, p < 0.001) and non-death censored graft survival (HR per 10% increase in (L)KDPI: 1.259, 95% CI: 1.164–1.361, p < 0.001) but not for the LKDPI in living donation (p < 0.001) and non-death censored graft survival , respectively. The (L)KDPI as a continuous variable was significantly associated with death censored graft survival (HR per 10% increase in (L)KDPI: 1.197, 95% CI: 1.085–1.320, donation . As dichThe estimated C-statistics of long-term death censored graft survival (5 years) was 0.692 (±0.042) for the (L)KDPI alone and 0.714 (±0.05) if IF/TA in the post reperfusion biopsy was included into the model. On the other hand, donor age alone also yielded a C-statistic of 0.662 (±0.043). The C-statistic of 1-year prediction of death censored graft survival was 0.775 (±0.046) for the (L)KDPI alone and 0.772 (±0.056) for (L)KDPI + IF/TA. In comparison, the C-statistics of donor age considering events within 1 year was 0.715 (±0.053).p = 0.025, p = 0.006). To exclude the bias of assignment of better kidney grafts to younger patients, we also fitted a Cox-regression for death censored graft survival to the data with the KDPI (only DBD), ECD-status, PRA, and the recipient's age as independent variables. Here also the KDPI showed a significant association . Interestingly, in all models including PRA, PRA also had a HR statistically significant from one, indicating its independent association from all other factors investigated on death censored graft survival. To investigate the known highly important association between the primary outcome and donor age, a Cox-regression was calculated for the (L)KDPI and donor age. In this model neither parameters could prove a significant association.Nonetheless, in a multivariate Cox-regression model the (L)KDPI was significantly associated with death censored graft survival if ECD-status, panel reactive antibodies (PRA) and cold ischemia time (CIT) were considered in the model (HR per 10% increase in (L)KDPI: 1.185, 95% CI: 1.033–1.360, p < 0.001) for all transplantations and 2.981  after DBD, respectively. Since there was only one living donation with an LKDPI >85%, we were not able to perform statistical analyses in this group. Thus, we decided to pool living and deceased donor kidneys into one analysis. Although 31% of the living donations were classified as ECD, there was no relevant difference between survival of ECD and SCD kidneys in living donations KDPI of ≤85% were classified as ECD whereas only 2 renal grafts >85% were classified as SCD . Survivar = 0.30, p < 0.001; arteriosclerosis r = 0.33, p < 0.001; IF/TA r = 0.28, p < 0,001). This was most likely due to the high number of deceased donations as only arteriosclerosis turned out to significantly correlate in living donations .To assess correlation of the (L)KDPI with the quality of the transplanted kidneys more accurately we included the histopathological findings in post-reperfusion biopsies into the statistical analyses as described above. Glomerulosclerosis, arteriosclerosis, and IF/TA as chronic lesions and ATI as renal hallmark of acute injury were histologically evaluated. Naturally, the extent of the chronic parameters increases with an increasing (L)KDPI . Fittingr = 0.198, p < 0.001, Furthermore, we found a moderate, but highly significant correlation between the (L)KDPI and the extent of ATI (p < 0.001), arteriosclerosis , and IF/TA  were significantly associated with the ECD status whereas ATI was not . In living donations no statistically significant associations between chronic lesions except arteriosclerosis and no association between ATI and the ECD status existed .Likewise, associations between the histopathological characteristics and the SCD/ECD-classification were apparent . GlomeruFirst, the application of the KDPI and the LKDPI turned out to be a useful tool in this European single center analysis to assess the quality of donor kidneys all in line with earlier reports KDPI against the background of the SCD/ECD-classification, which is more commonly used in Europe. We further compared this classification with baseline biopsies, which are routinely taken 10 min after the onset of reperfusion in our transplant center. The present study revealed the following major findings:  reports , 27. FurSecond, this trial at hand proved that KDPI and LKDPI enable transplant physicians to compare graft quality between living and deceased donation in a non-US transplant cohort, the way the LKDPI classification was originally defined for  this suggests a better assessment of ECD kidneys by use of the (L)KDPI with regards to the further probable course after transplantation. Therefore, it can be assumed that the more complex and gradient (L)KDPI, which is based on a bigger range of information, reduces the risk to discard a valuable organ as compared to the dichotomous SCD/ECD-classification. On the other hand, the estimated overall graft survival of KDPI kidneys >85% of only about 60% after 5 years emphasizes the question if these organs should be used for transplantation. ined for . Hence, ined for , 27, 28,ined for . Noteworined for . Fittingined for . Interesined for . ECD kidined for .Third, the (L)KDPI in the investigated cohort correlated well with chronic lesions such as arteriosclerosis, glomerulosclerosis and IF/TA giving reason to expected lower graft quality of marginal donor kidneys, which was shown previously KDPI and the degree of ATI as histological hallmark of renal IRI is present in this cohort. Earlier studies demonstrated that marginal and especially ECD kidneys are significantly more vulnerable to cold ischemia time, which is part of the transplantation process after deceased donation and the subsequent tubular injury . Finally, the retrospective design of this study cannot reach the quality of a prospective observation study.Our study has several points for critical discussion. We investigated on a single center cohort with a moderate number of cases including kidney transplantation after deceased as well after living donation. Comparison of DBD to living donors bears a risk for bias due to big differences in organ quality . HoweverIn conclusion, also in a European single center cohort the (L)KDPI for kidney transplants living donation and DBD is useful to assess organ quality more accurate than SCD/ECD-classification and to stratify their risk for later graft loss. Until this study there was no certainty, if the predictive value of the (L)KDPI translates into histopathological findings of baseline kidney biopsies. Additionally, the increase in Harrell's C after inclusion of IF/TA suggests an even better judgement of organ quality utilizing a biopsy. Thus, a prospective, multicenter study with a higher number of patients performing baseline biopsies is required to clarify, if the combination of the (L)KDPI and histopathological findings can improve the predicted outcome of kidney grafts. This might give clinicians the missing tool to better judge the value of grafts rendered as bad quality by current scores, since evidence proving the need to transplant these organs to improve patient survival accumulates , 49, 50.The raw data supporting the conclusions of this article are available from corresponding author upon reasonable request.The studies involving human participants were reviewed and approved by Ethics Committee of the Technical University of Munich, Germany. The patients/participants provided their written informed consent to participate in this study.QB and SK wrote the manuscript. SK and CS designed the concept of the study and profile index of the study. QB, FH, CT, and SK collected clinical data. QB, FH, BH, and SK performed and reviewed statistical analysis. VA is responsible for the routinely performance of surgical biopsies used in this study. MB-H analyzed the biopsies. VA, KA, LR, and UH oversaw the study and critically discussed the manuscript. All authors approved the submitted version of the manuscript.This work was supported by the Klinikum Rechts der Isar of the Technical University of Munich.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.


Variable stiffness joints have been gradually applied in rehabilitation robots because of their intrinsic compliance and greater ability to adjust mechanical stiffness. This paper designs a variable stiffness joint for upper limb rehabilitation training. The joint adopts the variable stiffness principle based special curved surface. The trapezoidal lead screw in the variable stiffness module has a self-locking function, and the stiffness can be maintained without the continuous output torque of the motor. In the aspect of control, back propagation (BP) neural network PID control strategy is used to control the torque of variable stiffness joint. Experiments show that this control method can effectively improve the torque control performance of variable stiffness joints in the case of low stiffness, and the isotonic centripetal resistance training can be realized by using the joints and control methods designed in this paper. Based on medical theory, the upper limb rehabilitation robot drives the affected limb to carry out scientific and effective training  can be divided into variable lever arm, special curved surface, changing the number of elastic elements and so on. The way of changing lever arm is to change the transmission ratio between load and spring according to the proportion of lever arm. It is mainly composed of load point, pivot and spring contact point. Changing any position can adjust the stiffness of the mechanism. For example, Chaichaowarat designed a variable stiffness spring mechanism, which is composed of a slider, a roller and an adjustable unsupported length leaf spring. The adjustment of the slider position changes the spring contact point, thus obtaining the variable stiffness characteristics , l0 is the initial compression of the spring, and kk is the spring stiffness coefficient.The slope k2 of Ft can be obtained:k3 of the tangential force Fn of the output flange can be obtained as:According to equations (2) and (5), the slope Tn, deformation angle of the variable stiffness joint α and the initial compression of the spring l0 can be obtained.According to equations (2)–(6), the functional relationship between the output torque x0 and y0 are functions of α, and it can be measured by the encoder.In equation (7), The expression of static stiffness of variable stiffness joint is:Tn, the deformation angle of the variable stiffness module α and the initial spring compression l0, which determines the stiffness characteristics of the joint. The initial compression l0 of the spring can be changed by the screw actuated by the stiffness adjustment motor to adjust the joint stiffness. Take the spring stiffness coefficient kk = 88 N/mm, the ellipse long axis a as 60 mm, and the short axis b as 30 mm. According to the above theoretical equation, the relationship curve between the output torque Tn, the deformation angle α and the spring compression l0 is shown in According to equation (7), the cam profile on the output flange determines the nonlinear relationship between the output torque l0, the greater the joint stiffness at the same joint deformation angle α. Finally, it is found that the range of joint deformation angle is 0–0.4 rad, the corresponding output torque range is 0–14 Nm, and the stiffness variation range is 0–35 Nm/rad, which meets the requirements of human elbow joint stiffness and torque output, ant it can used in elbow rehabilitation.It can be seen from In this section, a variable stiffness joint dynamic model is established to derive the joint transfer function. As shown in a satisfy the following relation:The torque of main motor τJa and Ca are the inertia and damping coefficient of the main motor, τ is the output torque of the main motor, θa is the output angle of the main motor. Torque and position at the output end of harmonic reducer are τb and θb. τa and θa satisfy the following relation,In equation (9), N is the harmonic reduction ratio, η is the transmission efficiency. In this joint mechanism, the flexible link only plays the role of transmitting torque, so the torque at both ends of the flexible link has the following relationship:In equation (10), cis the output torque of the flexible link, Jc is the equivalent inertia of the transmission system, Cc is the damping coefficient of the transmission system, Cs is the damping coefficient of the flexible element, θc is the rotation angle of the output end, τext is the external load torque. Finally, the dynamic model of variable stiffness joint can be obtained as:In equation (11), τThen the variable stiffness joint transfer function is:d. τd, τa and τc has the relationship as following,Generally, the traditional PID control method is adopted for the joint torque control, and the control command is τkp, ki and kd are proportional, integral and differential control parameters, respectively. At this time, the joint torque transfer function is:In equation (14), Ks, external load τext, torque command τd and PID gain parameters. Ks and τd are determined by the control command, and the external load τext is determined by the human-machine interaction torque. When the traditional PID control method is adopted, the fixed PID gain parameters are difficult to meet the torque control performance under different stiffness conditions, especially in the case of low stiffness, improper parameter adjustment will produce oscillation, slow response, large overshoot, long system stability time and other phenomena, which will reduce the safety of in rehabilitation training. Therefore, a PID control strategy based on BP neural network is designed as shown in From equations (12) and (13), it can be seen that the torque response of variable stiffness joint is related to joint stiffness Ks, external load τext and driving torque τd, so as to improve the real-time, accuracy and stability of torque response of joints under low stiffness furtherly. The specific implementation process is shown in Ks, τd, τext) as the input vector, the Ks parameter covers the range of 3–40 Nm/rad, the τd parameter covers the range of 0–20 Nm, and the τext parameter covers the range of 0–20 Nm/rad. In the case of finite set, the optimal kp, ki, kd parameters are used as the objective vector. Total 600 groups of samples . Optimized parameters are shown in BP off-line neural network can optimize the gain parameters of PID controller for three groups of variables: different joint stiffness a1 is the output of the first hidden layer, a2 is the output of the first output layer, p1 is the input vector of the first layer, IW1, 1 is the weight of the first hidden layer, b1 is the threshold of the first hidden layer, LW2, 1 is the weight of the first output layer, b2 is the threshold of the first output layer, 80% of the random samples are used as the training set, 10% of the samples are used as the verification set, and 10% of the samples are used as the test set for training. As shown in In equation (16), Finally, the PID torque control model based on BP neural network is built in Simulink for simulation analysis. Under the conditions of low stiffness (spring compression of 0 mm) and high stiffness (spring compression of 1 mm), the simulation results are compared with the traditional PID torque control, and the results are shown in In the experiment, the simulation platform developed by Links company is used, as shown in The host-computer in the experimental platform runs RT-sim and MATLAB/Simulink software. RT-sim software compiles the Simulink model into C code that can be executed under VxWorks system, and the host-computer is equipped with operation and monitoring modules. The slave-computer is composed of VxWorks, servo motor driver. VxWorks runs the program compiled by RT-sim, and sends the command to the motor servo driver to control the variable stiffness joint. At the same time, the sensor signals in the variable stiffness joint are collected to monitor the joint state.Firstly, the static torque of the variable stiffness joint is measured. When the joint is fixed, pull the rotating arm through the tension meter to rotate. The length of the rotating arm is 30 cm, and the joint deformation angle is measured by the rotary encoder. Under different initial spring compression, the joint rotates evenly between 0 and 0.35 rad by the same interval, and the measured tension value is recorded to obtain the variable stiffness joint torque. As the deformation angle increases, the joint torque shows an upward trend, and under the same torsion angle, the greater the spring compression, the greater the torque, and the greater the joint stiffness. Compared with the theoretical value in The torque control experiment was carried out under the conditions of low stiffness (spring compression of 0 mm) and high stiffness (spring compression of 1 mm). PID control and BP neural network based PID controller were used to carry out the step response experiment, and the step command was 3 Nm.As shown in Finally, the isometric resistance training experiment is carried out. The tester needs to overcome the resistance moment of the variable stiffness joint to complete the elbow flexion movement, and the extension movement is brought back to the initial position by the active torque provided by the variable stiffness mechanism, so as to complete the isometric centripetal resistance training by reciprocating motion. The experiment was divided into two groups. One group set the variable stiffness joint to provide a constant resistance torque of 8 Nm under the condition of high stiffness (spring compression 1 mm) and the other group under the condition of low stiffness (spring compression 0 mm).The driving joint of the traditional upper limb rehabilitation robot is rigid, which is difficult to ensure the safety and comfort of the rehabilitation process. To solve this problem, this paper proposes a variable stiffness joint applied to the elbow rehabilitation robot. The joint adopts the variable stiffness principle of special curved surface, and the trapezoidal screw in the joint has a self-locking function, and the stiffness can be maintained without the continuous output torque of the stiffness adjustment motor. In the control aspect, the BP neural network based PID controller is used to improve the torque control response performance by adjusting the gain parameters under different stiffness. The experimental platform of elbow rehabilitation robot with variable stiffness joint is built, and the isotonic centripetal resistance training experiment of elbow joint is carried out to verify the effect of BP neural network PID torque control. The future work will be combined with online neural network to match the elbow stiffness of patients in real time for resistance rehabilitation training.The original contributions presented in the study are included in the article/supplementary material, further inquiries can be directed to the corresponding author/s.BH: conceptualization, supervision, and project administration. BM: writing-original draft and visualization. SL: methodology and formal analysis. HY: supervision and project administration. All authors contributed to the article and approved the submitted version.This work was supported in part by National Key R&D Program of China (2020YFC2005800 and 2020YFC2005804), Natural Science Foundation of Shanghai (20ZR1437800), and Biomedical Science and Technology support project of Shanghai (22S31901400).The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.


Psychosis are complex disorders due to their symptomatic and evolutionary heterogeneity. The genetic-environmental interaction model is the most accepted etiopathogenic model, in which neurobiological processes  and environmental factors (for example: childhood trauma) are studied. The association between suffering traumatic events in childhood and the subsequent development of a Mental Disorder is of increasing interest.Analyze if a childhood trauma is a modulating factor of psychotic symptoms in patients with Mental Disorder. Analyze the implication of childhood trauma in long-term functionality.The sample is made up of 37 patients with psychosis and their healthy brothers. Different sociodemographic, clinical and evolutionary variables were collected in all groups. The sample was evaluated using the semi-structured interview CASH, the WHODAS scale and the self-applied questionnaire CTQ.We did not find significant differences between the scores of CTQ between patients with psychosis and their healthy brothers. Sexual abuse is significantly correlated with the presence of hallucinations, inappropriate affect, formal thought disorders and catatonic symptoms. Emotional neglect is significantly correlated with the presence of hallucinations, inappropriate affect, affective blunting, and anhedonia. Physical neglect is significantly correlated with flattery and blunt affection. Sexual abuse is correlated with poorer personal care. Emotional neglect is correlated with poorer personal care, poorer family functioning, and worse overall functioning in the last year.The intensity of traumatic experiences throughout childhood could be considered a modulating factor of psychotic symptoms  and overall functioning .