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The quality of resistance spot welding (RSW) joints is strongly affected by the condition of the electrodes. This work develops a machine learning-based tool to automatically assess the influence of electrode wear on the quality of RSW welds. Two different experimental campaigns were performed to evaluate the effect of electrode wear on the mechanical strength of spot welds. The resulting failure load of the joints has been used to define the weld quality classes of the machine learning tool, while data from electrode displacement and electrode force sensors, embedded in the welding machine, have been processed to identify the predictors of the tool. Some machine learning algorithms have been tested. The most performing algorithm, i.e., the neural network, achieved an accuracy of 90%. This work provides important theoretical and practical contributions. First, the decreasing thermal expansion of the weld nugget as the electrode degradation advances results in a strong correlation between the difference of the maximum displacement value and the last value recorded during the welding and the relative failure load. Then, this work offers a practical decision support tool for manufacturers. In fact, the automatic detection of low-quality welds allows to reduce or eliminate unnecessary redundant welds, which are performed to compensate for the uncertainty of electrode wear. This leads to savings in time, energy, and resources for manufacturers. Finally, general recommendations for the timing of redressing or replacing the electrode are provided in the manuscript based on the company willingness to accept some non-compliant welds or not. [ABSTRACT FROM AUTHOR]

Several computational methods have been developed to identify neutralizing antibodies (NAbs) covering four dengue virus serotypes (DENV-1 to DENV-4); however, limitations of the dataset and the resulting performance remain. Here, we developed a new computational framework to predict potent and stable NAbs against DENV-1 to DENV-4 using only antibody (CDR-H3) and epitope sequences as input. Specifically, our proposed computational framework employed sequence-based ML and molecular dynamic simulation (MD) methods to achieve more accurate identification. First, we built a novel dataset (n = 1108) by compiling the interactions of CDR-H3 and epitope sequences with the half maximum inhibitory concentration (IC50) values, which represent neutralizing activities. Second, we achieved an accurately predictive ML model that showed high AUC values of 0.879 and 0.885 by tenfold cross-validation and independent tests, respectively. Finally, our computational framework could be applied to filter approximately 2.5 million unseen antibodies into two final candidates that showed strong and stable binding to all four serotypes. In addition, the most potent and stable candidate (1B3B9_V21) was evaluated for its development potential as a therapeutic agent by molecular docking and MD simulations. This study provides an antibody computational approach to facilitate the high-throughput identification of NAbs and accelerate the development of therapeutic antibodies. [ABSTRACT FROM AUTHOR]

To realize economically feasible electrochemical CO2 conversion, achieving a high partial current density for value-added products is particularly vital. However, acceleration of the hydrogen evolution reaction due to cathode flooding in a high-current-density region makes this challenging. Herein, we find that partially ligand-derived Ag nanoparticles (Ag-NPs) could prevent electrolyte flooding while maintaining catalytic activity for CO2 electroreduction. This results in a high Faradaic efficiency for CO (>90%) and high partial current density (298.39 mA cm‒2), even under harsh stability test conditions (3.4 V). The suppressed splitting/detachment of Ag particles, due to the lipid ligand, enhance the uniform hydrophobicity retention of the Ag-NP electrode at high cathodic overpotentials and prevent flooding and current fluctuations. The mass transfer of gaseous CO2 is maintained in the catalytic region of several hundred nanometers, with the smooth formation of a triple phase boundary, which facilitate the occurrence of CO2RR instead of HER. We analyze catalyst degradation and cathode flooding during CO2 electrolysis through identical-location transmission electron microscopy and operando synchrotron-based X-ray computed tomography. This study develops an efficient strategy for designing active and durable electrocatalysts for CO2 electrolysis. A key factor for the electrochemical reduction of CO2 to CO is limiting the competing H2 evolution reaction. Here, authors use real-time synchrotron X-ray computed tomography to show that a silver nanoparticle-ligand catalyst structure improves water management, thereby maintaining CO production. [ABSTRACT FROM AUTHOR]

Olive flounder were immersed with viral hemorrhagic septicemia virus (VHSV) and reared for 30 days at 17℃ mount resistance against the virus, but the standard for the rearing period remains unclear. Here, we investigated VHSV dynamics and localization in internal organs (heart, spleen, and kidney) after VHSV immersion treatment and rearing at a suboptimal temperature (17℃), followed by rechallenge at an optimal temperature (10℃), and compared the protective efficacy between rearing periods of 5 days and 30 days at 17℃. Juvenile olive flounder reared for 5 days at 17℃ after VHSV immersion treatment acquired resistance against the VHSV infection, as evidenced by their 100% survival. The observed VHSV N gene mRNA in the kidney of flounder (5-day rearing) gradually increased and peaked at 15 days post re-challenge (dpr), although increased until 5 dpr and thereafter decreased in the kidney of flounder (30-day rearing). VHSV mRNA signal in flounder (5-day rearing) was observed at 15 dpr, whereas it was detected at 5 dpr in flounder (30-day rearing) by RNA-ISH (in-situ hybridization). The protection provided by live VHSV vaccination at suboptimal temperatures might not be mediated by humoral immunity, with evidence of lower IgM mRNA expression in the vaccinated group. These observations provide a better understanding of the rearing period needed for immunizing fish against the virus at suboptimal temperatures. [ABSTRACT FROM AUTHOR]

The yellow fever 17D vaccine (YF17D) is highly effective but is frequently administered to individuals with pre-existing cross-reactive immunity, potentially impacting their immune responses. Here, we investigate the impact of pre-existing flavivirus immunity induced by the tick-borne encephalitis virus (TBEV) vaccine on the response to YF17D vaccination in 250 individuals up to 28 days post-vaccination (pv) and 22 individuals sampled one-year pv. Our findings indicate that previous TBEV vaccination does not affect the early IgM-driven neutralizing response to YF17D. However, pre-vaccination sera enhance YF17D virus infection in vitro via antibody-dependent enhancement (ADE). Following YF17D vaccination, TBEV-pre-vaccinated individuals develop high amounts of cross-reactive IgG antibodies with poor neutralizing capacity. In contrast, TBEV-unvaccinated individuals elicit a non-cross-reacting neutralizing response. Using YF17D envelope protein mutants displaying different epitopes, we identify quaternary dimeric epitopes as the primary target of neutralizing antibodies. Additionally, TBEV-pre-vaccination skews the IgG response towards the pan-flavivirus fusion loop epitope (FLE), capable of mediating ADE of dengue and Zika virus infections in vitro. Together, we propose that YF17D vaccination conceals the FLE in individuals without prior flavivirus exposure but favors a cross-reactive IgG response in TBEV-pre-vaccinated recipients directed to the FLE with potential to enhance dengue virus infection. Flavivirus infection or vaccination can induce cross-reactive immune responses. Here, the authors show how previous immunization with the tick-borne encephalitis virus vaccine affects the immune response to the yellow fever vaccine, suggesting that the yellow fever vaccine virus conceals epitopes shared with other flaviviruses in flavivirus-naive but not flavivirus-pre-exposed individuals. [ABSTRACT FROM AUTHOR]

The yellow fever 17D vaccine (YF17D) is highly effective but is frequently administered to individuals with pre-existing cross-reactive immunity, potentially impacting their immune responses. Here, we investigate the impact of pre-existing flavivirus immunity induced by the tick-borne encephalitis virus (TBEV) vaccine on the response to YF17D vaccination in 250 individuals up to 28 days post-vaccination (pv) and 22 individuals sampled one-year pv. Our findings indicate that previous TBEV vaccination does not affect the early IgM-driven neutralizing response to YF17D. However, pre-vaccination sera enhance YF17D virus infection in vitro via antibody-dependent enhancement (ADE). Following YF17D vaccination, TBEV-pre-vaccinated individuals develop high amounts of cross-reactive IgG antibodies with poor neutralizing capacity. In contrast, TBEV-unvaccinated individuals elicit a non-cross-reacting neutralizing response. Using YF17D envelope protein mutants displaying different epitopes, we identify quaternary dimeric epitopes as the primary target of neutralizing antibodies. Additionally, TBEV-pre-vaccination skews the IgG response towards the pan-flavivirus fusion loop epitope (FLE), capable of mediating ADE of dengue and Zika virus infections in vitro. Together, we propose that YF17D vaccination conceals the FLE in individuals without prior flavivirus exposure but favors a cross-reactive IgG response in TBEV-pre-vaccinated recipients directed to the FLE with potential to enhance dengue virus infection. Flavivirus infection or vaccination can induce cross-reactive immune responses. Here, the authors show how previous immunization with the tick-borne encephalitis virus vaccine affects the immune response to the yellow fever vaccine, suggesting that the yellow fever vaccine virus conceals epitopes shared with other flaviviruses in flavivirus-naive but not flavivirus-pre-exposed individuals. [ABSTRACT FROM AUTHOR]