Background: In 80% of patients, COVID-19 presents as mild disease^1,2. 20% of cases develop severe (13%) or critical (6%) illness. More severe forms of COVID-19 present as clinical severe acute respiratory syndrome, but include a T-predominant lymphopenia³, high circulating levels of proinflammatory cytokines and chemokines, accumulation of neutrophils and macrophages in lungs, and immune dysregulation including immunosuppression⁴. Methods: All major SARS-CoV-2 proteins were characterized using an amino acid residue variation analysis method. Results predict that most SARS-CoV-2 proteins are evolutionary constrained, with the exception of the spike (S) protein extended outer surface. Results were interpreted based on known SARS-like coronavirus virology and pathophysiology, with a focus on medical countermeasure development implications. Findings: Non-neutralizing antibodies to variable S domains may enable an alternative infection pathway via Fc receptor-mediated uptake. This may be a gating event for the immune response dysregulation observed in more severe COVID-19 disease. Prior studies involving vaccine candidates for FCoV^5,6 SARS-CoV-1^7-10 and Middle East Respiratory Syndrome coronavirus (MERS-CoV) ¹¹ demonstrate vaccination-induced antibody-dependent enhancement of disease (ADE), including infection of phagocytic antigen presenting cells (APC). T effector cells are believed to play an important role in controlling coronavirus infection; pan-T depletion is present in severe COVID-19 disease³ and may be accelerated by APC infection. Sequence and structural conservation of S motifs suggests that SARS and MERS vaccine ADE risks may foreshadow SARS-CoV-2 S-based vaccine risks. Autophagy inhibitors may reduce APC infection and T-cell depletion^{12 13}. Amino acid residue variation analysis identifies multiple constrained domains suitable as T cell vaccine targets. Evolutionary constraints on proven antiviral drug targets present in SARS-CoV-1 and SARS-CoV-2 may reduce risk of developing antiviral drug escape mutants. Interpretation: Safety testing of COVID-19 S protein-based B cell vaccines in animal models is strongly encouraged prior to clinical trials to reduce risk of ADE upon virus exposure.

Background: Dengue is the most common arthropod-borne sickness worldwide, impacting at least 50 million people each year. The dengue virus has four primary serotypes. Infection with one serotype confers homotypic immunity but not heterologous immunity, and secondary infections may be more severe. Although blood transfusions and organ donations have also been observed, the Aedes aegypti mosquito is the primary vector for the transmission of dengue. Infection causes a continuum of clinical illness, from asymptomatic infection to dengue fever, DHF, and dengue shock syndrome (DSS).Aim: To assess the presence of anti DENV IgG and anti DENV IgM antibodies specific to the four dengue serotypes in blood donor service donors and the importance of pre-donation screening in routine blood collection procedures.Method: 3 mL of peripheral venous blood from 507 blood donors was collected in tubes with BD vacutainer gel tube for serum separation after epidemiological records were reviewed. After that, serum was separated and tests were performed by SD Bioline Dengue Duo. Participants in the study completed a social and epidemiological questionnaire that contained information such as age, gender, and dengue diagnosis.Result: Out of the 507 blood samples that were taken, 473 (93.3%) came from male blood donors, while the remaining 34 (6.7%) belonged to female blood donors. The ratio of males to females is 13.91 to 1. The age range is 18–60 years, and the mean and standard deviation are both 27.7 and 6.5. 183 of the 507 samples produced anti DENV IgG positivity, while 324 did not. The ratio of positive to negative was 1.25:2.Conclusion: According to the findings of this study, quantitative methods for determining the presence of anti-dengue antibodies or detecting the dengue virus in blood donors in endemic areas should be devised in order to ensure the quality of blood transfusions.

ccJE+Advax is an inactivated cell culture Japanese encephalitis (JE) vaccine formulated with Advax™, a novel polysaccharide adjuvant based on delta inulin. This vaccine has previously shown promise in murine and equine studies and the current study sought to better understand its mechanism of action and assess the feasibility of single dose vaccine protection. Mice immunised with ccJE-Advax had higher serum neutralisation titres than those immunised with ccJE alone or with alum adjuvant. ccJE+Advax induced extraordinarily broad cross-neutralising antibodies against multiple flaviviruses including West Nile virus (WNV), Murray Valley Encephalitis Virus (MVEV), St Louis Encephalitis virus (SLE) and Dengue-1 and -2 viruses. Notably, the DENV-2 cross-neutralising antibodies from ccJE+Advax immunised mice uniquely had no DENV-2 antibody dependent enhancement (ADE) activity, by contrast to high ADE activity seen with DENV-1 cross-reactive antibodies induced by mbJE or ccJE alone or with alum adjuvant. JEV-stimulated splenocytes from ccJE+Advax immunised mice showed increased IL-17 and IFN-γ production, consistent with a mixed Th1 and Th17 response, whereas ccJE-alum was associated with production of mainly Th2 cytokines. There is an ongoing lack of human vaccines against particular flaviviruses, including WNV, SLE and MVEV. Given its ability to provide single-dose JEV protection as well as to induce broadly neutralising antibodies free of ADE activity, ccJE+Advax vaccine could be highly useful in all situations where rapid protection is desirable but ADE needs to be avoided, e.g. during a local outbreak or for use in travellers or the military requiring rapid travel to JEV endemic regions.

The vast majority of antibodies generated against a virus will be non-neutralising1. However, this does not denote an absence of protective capacity. Yet, within the field there is typically a large focus on antibodies capable of directly blocking infection (neutralising antibodies, nAbs) of either specific viral strains or multiple viral strains (broadly-neutralising antibodies, bnAbs). More recently, a focus on non-neutralising antibodies (nnAbs), or neutralisation-independent effects of nAbs, has emerged. These can have additive effects on protection or in some cases, be a major correlate of protection. As their name suggests, nnAbs do not directly neutralise infection but instead, through their Fc domains, may mediate interaction with other immune effectors to induce clearance of viral particles or virally infected cells. nnAbs may also interrupt viral replication within infected cells. Developing technologies of antibody modification and functionalisation may lead to innovative biologics that harness the activities of nnAbs for antiviral prophylaxis and therapeutics. In this review, we discuss specific examples of nnAb actions in viral infections where they have known importance. We also discuss the potential detrimental effects of such responses. Finally, we explore new technologies for nnAb functionalisation to increase efficacy or introduce favourable characteristics for their therapeutic applications.

Dengue fever is a viral mosquito-borne infection, a major international public health concern. With 2.5 billion people at risk of acquiring the infection around the world, disease severity is influenced by the immunological status of the individual, seronegative or seropositive, prior to natural infection. Caused by four antigenically related but distinct serotypes, DENV-1 to DENV-4, infection by one serotype confers life-long immunity to that serotype and a period of temporary cross-immunity (TCI) to other serotypes. The clinical response on exposure to a second serotype is complex with the so-called Antibody-Dependent enhancement (ADE) process, a disease augmentation phenomenon when pre-existing antibodies to previous dengue infection do not neutralize but rather enhance the new infection, used to explain the etiology of severe disease. In this paper, we present a minimalistic mathematical model framework developed to describe qualitatively the dengue immunological response mediated by antibodies. Three models are analyzed and compared: i) primary dengue infection, ii) secondary dengue infection with the same (homologous) dengue virus and iii) secondary dengue infection with a different (heterologous) dengue virus. We explore the features of viral replication, antibody production, and infection clearance over time. The model is developed based on body cells and free virus interactions resulting in infected cells activating antibody production. Our mathematical results are qualitatively similar to the ones described in the empiric immunology literature, providing insights on the immunopathogenesis of severe disease. Results presented here are of use for future research directions to evaluate the impact of dengue vaccines.

Before the emergence of SARS-CoV-1, MERS-CoV, and most recently SARS-CoV-2, al-ready four other coronaviruses have been circulating in the human population. The alpha coronaviruses NL63 and 229E and the beta coronaviruses OC34 and HKU1. These circulating coronaviruses all cause mild respiratory illness during the winter seasons and most people are already infected in early life. Could antibodies and/or T cells, es-pecially against the beta coronaviruses have offered some form of protection against SARS-CoV-2? Related is the question whether survivors of SARS-CoV-1 or MERS-CoV would be relatively protected against SARS-CoV-2. More importantly, would humoral and cellular immunological memory, generated during the SARS-CoV-2 pandemic, ei-ther by infection or vaccination offer protection against future coronaviruses? Or rather than protection, could antibody dependent enhancement have taken place, a mecha-nism by which circulating corona antibodies enhance the severity of COVID-19? An-other related phenomenon, the original antigen sin, would also predict that the effec-tivity of the immune response to future coronaviruses would be impaired because of reactivation of memory against irrelevant epitopes. Current available evidence indicates that latter scenarios are highly unlikely and that especially cytotoxic memory T cells directed against conserved epitopes of human coronaviruses could at least offer partial protection against future coronaviruses.

The high level of dengue virus (DENV) seroprevalence in areas where Zika virus (ZIKV) is circulating and the cross-reactivity between these two viruses have raised concerns on the risk of increased ZIKV disease severity for patients with a history of previous DENV infection. To determine the role of DENV pre-immunity in ZIKV infection, we analysed the T and B cell responses against ZIKV in donors with or without previous DENV infection. Using PBMCs from donors living in an endemic area in Colombia, we have identified, by interferon (IFN)-γ enzyme-linked immunospot (ELISPOT) assay, most of the immunodominant ZIKV T-cell epitopes in the non-structural proteins NS1, NS3 and NS5. Analyses of the T and B-cell responses in the same donors revealed a stronger T-cell response against peptides conserved between DENV and ZIKV, with a higher level of ZIKV-neutralizing antibodies in DENV-immune donors, in comparison with DENV-naïve donors. Strikingly, the potential for antibody mediated enhancement of ZIKV infection was reduced in donors with sequential DENV and ZIKV infection in comparison with donors with DENV infection only. Altogether, these data suggest that individuals with DENV immunity present improved immune responses against ZIKV.

Two monoclonal antibodies (mAbs) against human epidermal growth factor receptor 2 (HER2), trastuzumab and pertuzumab, were clinically approved. We previously developed a highly sensitive and specific anti-HER2 mAb, H2Mab-139 (mouse IgG1, kappa). In this study, we produced a defucosylated IgG2a version of anti‑HER2 mAb (H2Mab-139-mG2a-f) to enhance ADCC-mediated antitumor activity. H2Mab-139-mG2a-f exhibits a high binding affinity in flow cytometry with the dissociation constant (KD) determined to be 3.9 × 10‑9 M and 7.7 × 10‑9 M against HER2‑overexpressed Chinese hamster ovary (CHO)-K1 (CHO/HER2) and HER2-positive BT-474 cells, respectively. Moreover, we showed that H2Mab-139-mG2a-f exerted ADCC and complement-dependent cytotoxicity against CHO/HER2 and BT-474 cells in vitro and exhibited potent antitumor activities in the xenograft models. These results indicated that H2Mab-139-mG2a-f exerts antitumor effects against HER2-positive human breast cancers and could be useful for an antibody treatment regimen for HER2-positive human cancers.

The epithelial cell adhesion molecule (EpCAM) is a stem cell and carcinoma antigen, which mediates cellular adhesion and proliferative signaling by the proteolytic cleavage. In contrast to low expression in normal epithelium, EpCAM is frequently overexpressed in various carcinomas, which correlates with poor prognosis. Therefore, EpCAM has been considered as a promising target for tumor diagnosis and therapy. Using the Cell-Based Immunization and Screening (CBIS) method, we previously established an anti‐EpCAM monoclonal antibody (EpMab-37; mouse IgG1, kappa). In this study, we investigated the antibody‐dependent cellular cytotoxicity (ADCC), complement‐dependent cytotoxicity (CDC), and an antitumor activity by a defucosylated mouse IgG2a-type of EpMab-37 (EpMab-37-mG2a-f) against an EpCAM‐expressing breast cancer cell line (BT-474). EpMab-37-mG2a-f recognized BT-474 cells with a moderate binding-affinity [a dissociation constant (KD): 2.9x10-8 M] by flow cytometry. EpMab-37-mG2a-f exhibited ADCC and CDC for BT-474 cells by murine splenocytes and complements, respectively. Furthermore, administration of EpMab-37-mG2a-f significantly suppressed the BT-474 xenograft tumor development compared with the control mouse IgG. These results indicated that EpMab-37-mG2a-f exerts antitumor activities against the BT-474 xenograft, and could provide valuable therapeutic regimen for the breast cancers.

We previously developed a highly sensitive and specific anti-PDPN mAb, LpMab-23 (mouse IgG1, kappa). In this study, we produced a humanized IgG1 version (humLpMab-23) and its defucosylated form (humLpMab-23-f) of an anti‑PDPN mAb to potentiate the ADCC activity. The humLpMab-23 could recognize PDPN‑overexpressed Chinese hamster ovary (CHO)-K1 (CHO/PDPN) and PDPN-positive PC-10 and LN319 cells by flow cytometry. Furthermore, we found that humLpMab-23-f exerted ADCC and complement-dependent cytotoxicity against CHO/PDPN, PC-10 and LN319 cells in vitro and exhibited potent antitumor activities in the xenograft models. These results indicated that humLpMab-23-f could be useful for an antibody treatment regimen for PDPN-positive human cancers.

Antibody-dependent cell-mediated cytotoxicity (ADCC) by natural killer (NK) lymphocytes eliminates cells infected with viruses. Antiviral ADCC requires three components: 1) antibody; 2) effector lymphocytes with the Fc-IgG receptor CD16A; and 3) viral proteins in infected cell membranes. Fc-afucosylated antibodies bind with greater affinity to CD16A than fucosylated antibodies; individuals’ variation in afucosylation contributes to differences in ADCC. Current assays for afucosylated antibodies involve expensive methods. We report an improved bioassay for antibodies that support ADCC which encompasses afucosylation. This assay utilizes externalization of CD107a by NK-92-CD16A cells after antibody recognition. We used anti-CD20 monoclonal antibodies, GA101 WT or glycoengineered (GE), 10% or ~50% afucosylated, and CD20-positive Raji target cells. CD107a increased detection 7-fold compared to flow cytometry to detect Raji-bound antibodies. WT and GE antibody effective concentrations (EC50s) for CD107a externalization differed by 20-fold, with afucosylated GA101-GE more detectable. The EC50s for CD107a-externalization vs. 51Cr cell death were similar for NK-92 CD16A and blood NK cells. Notably, the %CD107a-positive cells negatively correlated with dead Raji cells and was nearly undetectable at high NK:Raji ratios required for cytotoxicity. This bioassay is very sensitive and adaptable to assess anti-viral antibodies but unsuitable as a surrogate assay to monitor cell death after ADCC.

Initial attempts to develop monoclonal antibodies as therapeutics to resolve influenza infections focused mainly on searching for antibodies with the potential to neutralise the virus in vitro with classical haemagglutination inhibition and micro-neutralisation assays. This led to the identification of many antibodies that bind to the head domain of haemagglutinin (HA) which generally have potent neutralisation capabilities that block viral entry or viral membrane fusion. However, this class of antibodies has a narrow breadth of protection in that they are usually strain specific. This led to the emphasis on stalk targeting antibodies which are able to bind a broad range of viral targets that span across different influenza subtypes. Recently, a third class of antibodies targeting the vestigial esterase (VE) domain have been characterised. In this review, we describe the key features of neutralising VE targeting antibodies and compare them with head and stalk class antibodies.

Despite successful vaccination efforts, the emergence of new SARS-CoV-2 variants poses ongoing challenges to control COVID-19. Understanding humoral responses concerning SARS-CoV-2 infections and their impact is crucial for developing future vaccines that are effective worldwide. Here, we identified 41 immunodominant linear IgG B-cell epitopes in its Spike glycoprotein with a SPOT synthesis peptide array probed with a pool of serum from hospitalized COVID-19 patients. Bioinformatics showed a restricted set of epitopes unique to SARS-CoV-2 compared to other coronavirus family members. Potential crosstalk was also detected with Dengue virus (DENV), confirmed by screening individuals infected with DENV before the COVID-19 pandemic in a commercial ELISA assay for anti-SARS-CoV-2 antibodies. Higher reactivity indices were often measured in individuals with a pre-pandemic dengue infection than those with COVID-19. A high-resolution evaluation of antibody reactivity against peptides representing epitopes in the spike protein identified ten sequences in the NTD, RBD, and S2 domains. Functionally, antibody-dependent enhancement (ADE) in SARS-CoV-2 infection of monocytes was observed with pre-pandemic dengue-positive sera. A significant increase in viral load was measured compared to controls, with no detectable neutralization or considerable cell death, suggesting its role in viral entry. This study highlights the importance of identifying the epitopes generated during the humoral response to a pathogenic infection to understand the potential interplay of previous and future conditions on disease. Vaccine development and optimization strategies should be mindful of the potential for A.D.E. that could differ geographically due to endemic biological risks.

Antibody-based passive immunotherapy has been used effectively in the therapy and prophylaxis of infectious diseases. Outbreaks of the emerging viral infections from arthropod-borne viruses (arboviruses) represent a global public health problem due to the rapid spread and urge actions and treatment of the infected individuals to combat them. Preparedness in advance developing antivirals and studies related to the epidemiology could protect us from damages and losses. Immunotherapy based on monoclonal antibodies (mAbs) has shown to be very specific to combat infectious diseases and several illnesses. Recent advances in the mAb discovery techniques allowed the development and approval of a wide number of therapeutic mAbs. This review focuses on the technological approaches available to select neutralizing mAbs for emerging arbovirus infections and outstanding strategies to obtain highly effective and potent mAbs. The characteristics of mAbs developed as prophylactic and therapeutic antiviral agents for the dengue, Zika, chikungunya and West Nile virus are presented, as well as the protective effect verified in animal model studies.

: (1) Background: Healthcare workers (HCWs) are a well-known risk group for coronavirus infections with increased working hours in a potentially infectious environment. We evaluated both IgG and Neutralizing antibody levels, with IgG avidity index and persistence among health workers. (2) Methods: 1001 HCWs were tested for both IgG and Neutralizing antibodies. IgG avidity testing and one-year follow-up testing were done on selected HCWSs. (3) Results: COVID-19 IgG antibody levels were high among 299 (94.62%) HCWs with a history of COVID-19 infection (p <0.0001) compared with 479 (69.92%) HCWs who were not infected with COVID-19 during the first and second wave. A total of 899 (89.81%) HCWs had more than 50% neutralizing antibodies while the remaining 102 (10.19%) HCWs had less than 50% of Neutralizing antibodies. The avidity index was maintained at almost 40% (Gray zone). Both antibody levels were found markedly increased after one year when compared to initial results. (4) Conclusions: Healthcare workers are at a 2.29-fold higher risk of infection; Two folds higher IgG levels in HCWs involved in COVID-19 duty and their persistence for a longer time than in other groups signifies IgG antibody role in the prevention of severe disease in HCWs involved in Covid-19 patient care.

The presence of anti SARS-CoV2-RBD antibody (Anti-RBD) prevents severe COVID-19. We aimed to determine the accuracy of a point-of-care Anti-RBD test implemented in person living with HIV (PLWH), systemic lupus erythematosus (SLE), and chronic kidney disease (CKD). We enrolled 182 non-comorbid subjects and 335 persons with comorbid (PLWH, SLE, CKD) to test anti-RBD assay compared to surrogate viral neutralization (SVNT) as the reference test. We performed linear correlation analysis between anti-RBD vs SVNT and a ROC analyses to ascertain anti-RBD cut-off at 30%, 60%, and 90% inhibition of SVNT to calculate accuracy. Correlations of anti-RBD to SVNT among all groups were excellent with R= 0.7903, R=0.7843, R=0.8153 among non-comorbid, SLE and CKD groups, respectively, with significantly higher correlation among the PLWH group (R=0.8877; p-value=0.0072) compared to non-comorbid group. The accuracy of the anti-RBD test among PLWH and CKD group was similar with the non-comorbid but showed lower sensitivity in the SLE group (p=0.000014). The specificity of the test remained high in all groups. In conclusion, the Anti-RBD test had excellent correlation to SVNT. The persistently high specificity in all groups suggests that this test can be reliably utilized to detect presence of low neutralization capacity, prompting additional vaccination.

The epithelial cell adhesion molecule (EpCAM) is a cell surface glycoprotein, which is widely expressed on normal and cancer cells. EpCAM is involved in cell adhesion, proliferation, survival, stemness, and tumorigenesis. Therefore, EpCAM is thought to be a promising target for cancer diagnosis and therapy. In this study, we established anti-EpCAM monoclonal antibodies (mAbs) using the Cell-Based Immunization and Screening (CBIS) method. We characterized them using flow cytometry, western blotting, and immunohistochemistry. One of the established recombinant anti-EpCAM mAbs, recEpMab-37 (mouse IgG1, kappa), reacted with EpCAM-overexpressed Chinese hamster ovary-K1 cells (CHO/EpCAM) or a colorectal carcinoma cell line (Caco-2). In contrast, recEpMab-37 did not react with EpCAM-knocked out Caco-2 cells. The KD of recEpMab-37 for CHO/EpCAM and Caco-2 was 2.0 × 10-8 M and 3.2 × 10-8 M, respectively. In western blot analysis, recEpMab-37 detected EpCAM of CHO/EpCAM and Caco-2 cells. Furthermore, recEpMab-37 could stain formalin-fixed paraffin-embedded colorectal carcinoma tissues by immunohistochemistry. Taken together, recEpMab-37, established by CBIS method, is useful for detecting EpCAM in various applications.

Duct-dependent lesions are classically divided into duct dependent pulmonary circulation which involves severe right sided obstructive lesions such as pulmonary atresia or critical stenosis, and duct dependent systemic circulation which is characterized by malformation of the left side of the heart, and whose severest spectrum is hypoplastic left heart syndrome. Dextro-transposition of the great arteries remains in gray zone between being included in some old classifications as a duct dependent pulmonary circulation lesion or a new category of duct-dependent or independent mixing lesion. We hypothesize that re-classifying duct dependent congenital defects into duct dependent perfusion and oxygenation offers a model to fit D-TGA into the same category of right sided obstructive lesions and reflects the clinical spectrum in a more comprehensive way.

During the SARS-CoV-2 pandemic, many virus-binding monoclonal antibodies have been developed for clinical and diagnostic purposes. This underlines the importance of antibodies as universal bioanalytical reagents. However, little attention is given to the reproducibility crisis that scientific studies are still facing to date. In a recent study, not even half of all research antibodies mentioned in publications could be identified at all. This should spark more efforts in the search for practical solutions for the traceability of antibodies. For this purpose, we used thirty-five monoclonal antibodies against SARS-CoV-2 to demonstrate how sequence-independent antibody identification can be achieved by simple means applied onto the protein. First, we examined the intact and light chain masses of the antibodies relative to the reference material NIST-mAb 8671. Already half of the antibodies could be identified based solely on these two parameters. In addition, we developed two complementary peptide mass fingerprinting methods with MALDI-TOF-MS that can be performed in 45 minutes and had a combined sequence coverage of over 80%. One method is based on the partial acidic hydrolysis of the protein by 5 mM of sulfuric acid at 99 °C. Furthermore, we established a fast way for a tryptic digest without an alkylation step. We were able to show that the distinction of clones is possible simply by a brief visual comparison of the mass spectra. In this work, two clones originating from the same immunization gave the same fingerprints. Later, a hybridoma sequencing confirmed the sequence identity of these sister clones. In order to automate the spectral comparison for larger libraries of antibodies, we developed the online software ABID 2.0 (https://gets.shinyapps.io/ABID/). This open-source software determines the number of matching peptides in the fingerprint spectra. We propose that publications and other documents critically relying on monoclonal antibodies with unknown amino acid sequences should include at least one antibody fingerprint. By fingerprinting an antibody in question, its identity can be confirmed by comparison with a library spectrum at any time and context.

Tumor necrosis factor-α (TNFα), one of the major pro-inflammatory cytokines, plays a key role in an effective immune response. However, the chronic presence of TNFα can lead to several inflammatory disorders like rheumatoid arthritis, psoriasis, Crohn’s disease etc. Inhibition of TNFα by pharmacological inhibitors or antibodies has proven to be effective in palliative treatment to some extent. The aim of this study was to develop an anti-TNFα antibody which may be used as a therapeutic option to inhibit TNFα-mediated cytotoxicity. We characterized several hybridoma clones secreting monoclonal antibodies (mAbs) to human-TNFα. Four mAbs rescued L929 fibroblast cells from TNFα-triggered cell death and one of these, namely C8 was found to have the highest affinity. To gain insights into the mechanism by which mAb C8 inhibits human TNFα-mediated toxicity, the epitope corresponding to the mAb was delineated. The antigenic determinant was found to comprise of the stretch of amino acids 99-120, of which, 102-104 (QRE) form the core epitope. The observation was supported by bioinformatics analyses of an antigen-antibody complex model. In addition, the binding affinity of mAb C8 to TNFα was found to be comparable with that of Infliximab which is a commercially available anti TNFα mAb.

The cyclin-dependent kinase (Cdk) 1–cyclin B (CycB) complex plays critical roles in cell cycle regulation. Before Drosophila male meiosis, CycB is exported from the nucleus to the cytoplasm via the nuclear porin 62kD (Nup62) subcomplex in the nuclear pore complex. When this is inhibited, Cdk1 is not activated, and meiosis does not initiate. We investigated the mechanism that controls cellular localization and activation of Cdk1. Cdk1–CycB continuously shuttled into and out of the nucleus in the prolonged G2 phase before meiosis. Overexpression of CycB, but not that with nuclear localization signal sequences, rescued reduced cytoplasmic CycB and inhibition of meiosis in Nup62-silenced cells. Full-scale Cdk1 activation occurred in the nucleus shortly after its rapid nuclear entry. Cdk1-dependent centrosome separation did not occur in Nup62-silenced cells, while Cdk1 interacted with Cdk-activating kinase and Twine/Cdc25C in the nucleus of Nup62-silenced cells, suggesting the involvement of another suppression mechanism. Silencing of roughex rescued Cdk1 inhibition and initiated meiosis. Nuclear exports of Cdk1 ensured its escape from inhibition by cyclin-dependent kinase inhibitor. The complex reentered the nucleus via importin β at the onset of meiosis. We propose a model regarding the dynamics and activation mechanism of Cdk1–CycB to initiate male meiosis.

The major goal of this work is to present a novel fractional temperature-dependent boundary element model (BEM) for solving thermoelastic wave propagation problems in smart nanomaterials. The computing performance of the suggested methodology was demonstrated by using stable communication avoiding S-step – generalized minimal residual method (SCAS-GMRES) to solve discretized linear BEM systems. The benefits of SCAS-GMRES are investigated and compared to those of other iterative techniques. The numerical results are graphed to demonstrate the influence of fractional, piezoelectric, and length scale characteristics on total force-stresses. These findings also demonstrate that the BEM methodology is practical, feasible, effective, and has superiority over domain methods. The results of the present paper help to develop the industrial uses of smart nanomaterials.

This study addresses the critical challenge of Speech Enhancement (SE) in noisy environments, where the deployment of Deep Neural Networksolutions on microcontrollers is hindered by their extensive computational demands. Focusing on this gap, our research introduces a novel SE method optimized for MCUs, employing a 2-layer GRU model that capitalizes on perceptual speech properties and innovative training methodologies. By incorporating self-reference signals and a dual strategy of compression and recovery based on the Mel scale, we develop an efficient model tailored for low-latency applications. Our GRU-2L-128 model demonstrates a significant reduction in size and computational requirements, achieving a 14.2× decrease in model size and a 409.1× reduction in operations compared to traditional DNN methods like DCCRN, without compromising performance. This advancement offers a promising solution for enhancing speech intelligibility in resource-constrained devices, marking a pivotal step in SE research and application.

Guided image filter implicitly balances noise and details based on local variance, achieving noise suppression while preserving prominent edges. However, we have observed limitations in using variance to distinguish between noise and image details, resulting in the suppression of fine structures alongside noise. Furthermore, the goal of enhancing image details, which is crucial in image filtering, has not been adequately addressed in edge-preserving filter design. In this paper, we approach image filtering as a problem of spectral energy reconfiguration, where the gain of each spectral band is adaptively regulated to achieve simultaneous noise suppression and detail enhancement. Instead of relying on variance, we employ a linear noise estimator to obtain the Signal-to-Noise Ratio (SNR) measurement necessary for dynamic gain regulation. Similar to the guided image filter, we determine the filter coefficients by solving the closed-form solution of the optimizer. We demonstrate that the proposed extended guided filter effectively integrates information from multiple spectral bands locally, allowing for the joint enhancement of meaningful details while simultaneously smoothing noise.

Podocalyxin (PODXL) overexpression is associated with poor clinical outcomes in various tumors. PODXL is involved in tumor malignant progression through the promotion of invasiveness and metastasis. Therefore, PODXL has been considered as a promising target of monoclonal antibody (mAb)-based therapy. However, PODXL also plays an essential role in normal cells such as vascular and lymphatic endothelial cells.Therefore, cancer-specificity or selectivity is required for the reduction of adverse effects on normal cells. Here, we developed an anti-PODXL cancer-specific mAb (CasMab), PcMab-6 (IgG₁, kappa), by immunizing mice with soluble PODXL ectodomain derived from a glioblastoma LN229 cell.PcMab-6 reacted with the PODXL-positive LN229 cells, but not with PODXL-knockout LN229 cells in flow cytometry. Importantly, PcMab-6 recognized pancreatic ductal adenocarcinoma (PDAC) cell lines (MIA PaCa-2, Capan-2, and PK-45H), but did not react with normal lymphatic endothelial cells (LECs). In contrast, one of the non-CasMabs, PcMab-47 showed high reactivity to both the PDAC cell lines and LECs. Next, we engineered PcMab-6 into a mouse IgG_2a type (PcMab-6-mG_2a) and a humanized IgG₁-type (humPcMab-6) mAbs, and further produced the core fucose-deficient types (PcMab-6-mG_2a-f and humPcMab-6-f, respectively) to potentiate the antibody-dependent cellular cytotoxicity (ADCC). Both PcMab-6-mG_2a-f and humPcMab-6-f exerted ADCC and complement-dependent cellular cytotoxicity in the presence of effector cells and complements, respectively. In the PDAC xenograft model, both PcMab-6-mG_2a-f and humPcMab-6-f exhibited potent antitumor effects. These results indicated that humPcMab-6-f could apply to antibody-based therapy against PODXL-expressing pancreatic cancers.

PG16 is a broadly neutralizing antibody that binds to the gp120 subunit of the HIV-1 Env protein. The major interaction site is formed by the unusually long complementarity determining region (CDR) H3. The CDRH3 residue Tyr100H is known to represent a tyrosine sulfation site; however, this modification is not present in the experimental complex structure of PG16 with full-length HIV-1 Env. To investigate the role of sulfation for this complex, we modeled the sulfation of Tyr100H and compared the dynamics and energetics of the modified and unmodified complex by atomistic molecular dynamics simulations. Our results show that sulfation does not affect the overall conformation of CDRH3, but still enhances gp120 interactions both at the site of mutation and for the neighboring residues. This stabilization affects not only protein-protein contacts, but also the interactions between PG16 and the gp120 glycan shield. Further, we also investigated whether PG16-CDRH3 is a suitable template for the development of peptide mimetics. For a peptide spanning residues 93-105 of PG16 we obtained an experimental EC50 value of 3nM for the binding of gp120 to the peptide. This affinity can be enhanced by almost one order of magnitude by artificial disulfide bonding between residues 99 and 100F. In contrast, any truncation results in significantly lower affinity, suggesting that the entire peptide segment is involved in gp120 recognition. Their high affinity makes PG16-derived peptides useful building blocks for further optimization to obtain a potent inhibitor that efficiently blocks HIV-1 infection.

This paper describes a proposed fractional filter-based multi-scale underwater and hazy image enhancement algorithm. The proposed system combines a modified global contrast operator with fractional order-based multi-scale filters used to generate several images, which are fused based on entropy and standard deviation. The multi-scale-global enhancement technique enables fully adaptive and controlled colour correction and contrast enhancement without over exposure of highlights when processing hazy and underwater images. This in addition to illumination/reflectance estimation coupled with global and local contrast enhancement. The proposed algorithm is also compared with the most recent available state-of-the-art multi-scale fusion de-hazing algorithm. Experimental comparisons indicate that the proposed approach yields better edge and contrast enhancement results without halo effect, colour degradation and is faster and more adaptive than all other algorithms from the literature.

Breast Cancer (BC) is the second most common type of cancer worldwide and displays the highest cancer-related mortality among women worldwide. Targeted therapies have revolutionized the way BC has been treated in the last decades improving life expectancies of millions of women. Among the different molecular pathways that have been of interest for the development of targeted therapies are the Cyclin-Dependent Kinases (CDK). CDK inhibitors are a class of molecules that already exist in nature and those belonging to the INK4 protein family specifically inhibit the CDK4/6 proteins. CDK4/6 inhibitors specifically block the transition from the G1 to the S phase of the cell cycle by dephosphorylation of the retinoblastoma tumor suppressor protein. In the past four years CDK4/6 inhibitors palbociclib, ribociclib, and abemaciclib received their first FDA approval for the treatment of Hormone Receptor (HR)-positive and Human Epidermal growth factor Receptor 2 (HER2)-negative breast cancer after showing significant improvements in progression-free survival in the PALOMA-1, MONALEESA-2 and the MONARCH-2 randomized clinical trials, respectively. After the encouraging results from these clinical trials, CDK4/6 inhibitors have also been investigated in the other BC subtypes. In HER2-positive BC, combination of CDK4/6 inhibitors with HER2-targeted therapies showed promise in preclinical studies and their clinical evaluation is ongoing. Moreover, in triple-negative BC, CDK4/6 inhibitors efficacy has been investigated in combination with other targeted therapies or immunotherapies. This review summarizes the molecular background and clinical efficacy of CDK4/6 inhibitors as single agents or in combination with other targeted therapies for the treatment of BC. Future directions of ongoing clinical trials and predictive biomarkers will be further debated.

Viral diseases represent a major public health concern and an ever-present risk for developing into a future pandemic. Antiviral antibody therapeutics, either alone or in combination with other therapies, have emerged as valuable preventative and treatment options, including during a global emergency. Here we will discuss polyclonal and monoclonal antiviral antibody therapies, focusing on the unique biochemical and physiological properties that make them well suited as therapeutic agents. We will describe the methods of antibody characterization and potency assessment throughout development, highlighting similarities and differences between polyclonal and monoclonal products as appropriate. In addition, we will consider the benefits and challenges of antiviral antibodies when used in combination with other antibodies or other types of antiviral therapeutics. Lastly, we will discuss novel approaches to the characterization and development of antiviral antibodies and identify areas that would benefit from additional research.

Background: Identifying a specific threshold level of SARS-CoV-2 antibodies that confers protection in immunocompromised patients has been very challenging. The aim was to assess the threshold of 264 binding antibody units (BAU)/ml using four different SARS-CoV-2 antibody assays (Abbott, Beckman, Roche, and Siemens) and to establish a new optimal threshold of protection for each of the four antibody assays. Methods: This study was performed on data retrieved from 69 individuals, who received at least one dose of the Pfizer/BioNTech BNT162b2 or Moderna COVID-19 vaccine (Spikevax) at the Alphabio Laboratory in Marseille, France (European Hospital, Alphabio – Biogroup). The results were compared to the percent inhibition calculated using a functional surrogate of a standardized virus neutralization test (Genscript). Results: Samples from 69 patients were analyzed. For a reference cutoff of 264 BAU/ml, assays showed moderate to good overall concordance with Genscript: 87% concordance for Abbott, 78% for Beckman, 75% for Roche, and 88% for Siemens. Overall concordance increased consistently after applying new thresholds, i.e., 148 BAU/ml (Abbott), 48 (Beckman), 559 (Roche), and 270 (Siemens). Conclusion: We suggest specific adjusted thresholds (BAU/ml) for the four commercial antibody assays that are used to assess pre-exposure prophylaxis in immunocompromised patients.

A large proportion of chronic stroke survivors still struggle with upper limb (UL) problems in daily activities. We investigated clinical outcomes and assessed the quality of movement before and after a 5-hour error-enhancement training. The pilot study had a pre-post intervention design, recruiting 22 patients in the chronic phase post-stroke with UL motor impairments. Patients received 1-hour robot treatment for five days. Patients were assessed at baseline and after training, collecting (1) clinical (UL Fugl-Meyer assessment (FMA-UE)), action research arm test (ARAT), motor assessment scale UL and tone), (2) patient-reported (hand subscale of the stroke impact scale, motor activity log (MAL), visual analogue scale of pain and tone) and (3) kinematic (KINARM, BKIN Technologies Ltd., Canada) outcome measures. Our analysis revealed significant improvements (median im-provement (Q1-Q3); p<0.05) in (1) FMA-UE (1.0 (0.8–3.0), p<0.001) and ARAT (2 (0.8–2.0), p<0.001); (2) MAL amount of use (0.1 (0.0–0.3), p<0.001) and MAL quality of use (0.1 (0.1–0.5), p<0.001); (3) KINARM-evaluated position sense ((-0.45 (-0.81–0.09), p=0.030) after training. These findings provide insight into kinematic, clinical, and self-reported improvements in UL functioning after five hours of error-enhancement UL training.

The ethics of invertebrate research have largely been ignored compared to the consideration of higher order animals, but more recent focus has questioned this trend. Using biohybrid robotic jellyfish as a case study, we examine the ethical considerations of invertebrate work and provide recommendations for future guidelines. This paper starts with an overview of philosophical views of animal ethics, the current state of knowledge for invertebrate pain and nociception, and current ethical guidelines. Next, we delve into the case study and analogous precedents. Specifically, in prior studies, we developed biohybrid robotic jellyfish, which modified live moon jellyfish with microelectronic swim controllers for future applications in ocean monitoring. Although jellyfish possess no central nervous system, pain receptors, or nociceptors, we closely monitored their stress responses, using the precautionary and minimization principles in consideration of the 4Rs: reduction, replacement, refinement, and reproducibility. We also discuss ethical considerations related to our studies and suggest that public opinion of invertebrate research relies heavily on repugnance, including fears of ‘playing God’ or limiting the ‘free will’ of animals. These issues are also examined for prior bioethics cases, such as the RoboRoach, cyborg beetle, ‘microslavery’ of microbes, biohybrid robots incorporating tissues from sea slugs (which are known to possess nociceptors), and other tissue cutting experiments involving soft-bodied invertebrates. However, biohybrid robotic jellyfish pose further ethical questions of potential ecological consequences as ocean monitoring tools, such as the impact of electronic waste in the ocean. To conclude these evaluations, we recommend that publishers require brief ethical statements for invertebrate research, which can include the following: a scientific justification for the research, discussion of the 4Rs, and cost-benefit analysis. We also delineate the need for more research on pain and nociception in invertebrates, which can then be used to revise or validate current research standards. These actions provide a stronger basis for the ethical study of invertebrate species, with implications for individual, species-wide, and ecological impacts on animals, as well as for interdisciplinary studies in science, engineering, and philosophy.

Objective:The Glioma brain tumor detection and segmentation methods are proposed in this paper using machine learning approaches. Methods:The boundary edge pixels are detected using Kirsch’s edge detectors and then contrast adaptive histogram equalization method is applied on the edge detected pixels. Then, Ridgelet transform is applied on this enhanced brain image in order to obtain the Ridgelet multi resolution coefficients. Further, features are derived from the Ridgelet transformed coefficients and the features are optimized using Principal Component Analysis (PCA) method and these optimized features are classified into Glioma or non-Glioma brain images using Co-Active Adaptive Neuro Fuzzy Expert System (CANFES) classifier.Results:The proposed method with PCA and CANFES classification approach obtains 97.6% of se, 98.56% of sp, 98.73% of Acc, 98.85% of Pr, 98.11% of FPR and 98.185 of FNR, then the proposed Glioma brain tumor detection method using CANFES classification approach only.

Time evolution operators of a strongly ionizing medium are calculated by a time-dependent unitary transformation (TDUT) method. The TDUT method has been employed in quantum mechanical system composed of discrete states. This method is especially helpful for solving molecular rotational dynamics in quasi-adiabatic regimes because the strict unitary nature of the propagation operator allows us to set the temporal step size large; a tight limitation on the temporal step size ($\delta t <<1$) can be circumvented by the strict unitary nature. On the other hand, in a strongly ionizing system where the Hamiltonian is not Hermitian, the same approach cannot be directly applied because it is demanding to define a set of field-dressed eigenstates. In this study, the TDUT method was applied to the ionizing regime using the Kramers-Henneberger frame, in which the strong-field-dressed discrete eigenstates are given by the field-free discrete eigenstates in a moving frame. Although the present work verifies the method for a one-dimensional atom as a prototype, the method can be applied to three-dimensional atoms, and molecules exposed to strong laser fields.

LuBO3 crystallizes in the calcite type (CaCO3) structure and is a widely applied inorganic host for luminescent materials and scintillators. Even though many scientific works have been published concerning the optical properties of rare earth doped LuBO3, so far, no study of the emission spectra as function of the excitation energy of such orthoborates has been conducted. Therefore, this work deals with the photoluminescence of RE doped LuBO3 with RE = Ce3+, Eu3+, Gd3+, or Tb3+, while an emphasize is laid on the energy dependence of these four luminescent compounds.

Unidirectional flow of a fluid with pressure-dependent viscosity through a porous structure is considered when the viscosity-pressure relationship is an exponential function of a pressure power function in order to investigate effects of the viscosity-pressure relation on the flow characteristics. The flow is governed by the generalized Brinkman’s equation with constant permeability, and a model flow domain of flow down an inclined porous channel is chosen for the sake of studying flow behaviour. Although the current work considers flow in a constant permeability porous structure, it does represent a first step in studying the more general, flow through a variable permeability porous channel. The arising governing equations are solved numerically using MATLAB and the flow is simulated to illustrate the effects of fluid properties as well as flow and medium parameters on the velocity profiles and shear stress.

The goal of this study was to develop a rapid diagnostic kit for rheumatic disease and systemic lupus erythematosus (SLE) screening. A novel rapid vertical flow assay (VFA) was engineered and used to assay anti-nuclear (ANA) and anti-dsDNA (αDNA) autoantibodies from systemic lupus erythematosus (SLE) patients and healthy controls (HC). Observer scores and absolute signal intensities from the VFA were validated by ELISA. The rapid ten minute point of care VFA test engineered demonstrated a limit of detection of 0.5 IU/ml for ANA and αDNA autoantibodies in human plasma with inter-operator CV of 19% for ANA and 12% for αDNA. Storage stability was verified over a three-month period. When testing anti-dsDNA and ANA levels in 22 SLE and 18 HC serum samples, the duplex VFA revealed 95% sensitivity, 72% specificity and 84% accuracy in discriminating disease groups, comparable to the gold standard, ELISA. The rapid αDNA/ANA duplex VFA can potentially be used in primary care clinics for evaluating patients or at-risk subjects for rheumatic diseases and for planning follow-up testing. Given its low cost, ease and rapid turnaround, it can also be used to assess SLE prevalence estimates.

Podoplanin (PDPN) is a cell-surface mucin-like glycoprotein that plays a critical role in tumor development and normal development of the lung, kidney, and lymphatic vascular systems. PDPN is overexpressed in several tumors and is involved in their malignancy. PDPN induces platelet aggregation through binding to platelet receptor C-type lectin-like receptor 2. Furthermore, PDPN modulates signal transductions that regulate cell proliferation, differentiation, migration, invasion, epithelial to mesenchymal transition, and stemness, all of which are crucial for the malignant progression of tumor. In the tumor microenvironment (TME), PDPN expression is up-regulated in the tumor stroma, including cancer-associated fibroblasts (CAFs) and immune cells. CAFs play significant roles in the extracellular matrix remodeling and the development of immunosuppressive TME. Additionally, PDPN functions as a co-inhibitory molecule on T cells, indicating the involvement with immune evasion. In this review, we describe the mechanistic basis and diverse roles of PDPN in malignant progression of tumor and discuss the possibility of the clinical application of PDPN-targeted cancer therapy, including cancer-specific monoclonal antibodies, and chimeric antigen receptor T technologies.

Acute ischemic strokes are the third leading cause of death and the leading cause of neurological disability worldwide. The oxygen and glucose deprivation associated with ischemic strokes not only leads to neuronal cell death, but also increases the inflammatory response and decreases functional output of the brain. The only intervention approved by US Federal Drug and Food Administration for treatment of ischemic strokes is tissue plasminogen activator (tPA), however, such treatment can only be given within 4.5 hours of the onset of stroke-like symptoms. This narrow time-range limits its application, and it also might induce detrimental rather than beneficial effects to stroke patients by treatment of the tPA. In order to reduce the infarct volume of an acute ischemic stroke while increasing the time period for treatment, emerging therapies reveal great potential by targeting inflammation, growth factors, ion channels, and neurotransmitter receptors with monoclonal antibody (MAB). With successfully application in the treatment of cancer patient by MAB, in this review, we will focus on recent advances on stroke therapy by using MAB on the treatment of stroke by targeting inflammation, growth factors, ion channels, and neurotransmitter receptors. Therefore, developing specific MAB targeting the signaling pathway of stroke will contribute to stroke therapy.

Recent researches indicated that metal nanoparticles which have the unique optical properties can be used to enhance the spectral response of the photovoltaic modules. Since most of the nanoparticles have enhancement effects in a specific wavelength range, improving the spectral response of the photovoltaic modules in a broadband range is crucial for their applications in imaging, energy harvesting, and optical communication. In this study, flower-like silver particles are applied to achieve the enhancement effects in a broadband range. The optical absorption of photovoltaic modules is improved in a broad wavelength range of 400~2000 nm by immobilizing flower-like silver particles onto an amorphous Si p-i-n structure, and the peak responsivity of the spectral response is enhanced by about 10 times. Theoretical investigation further elaborates that the enhancement originates from the near-field effects of silver particles due to the interaction of different parts of the flower-like silver particles. Through these studies, we demonstrate that, utilizing the subwavelength silver particles with roughness surface can achieve the spectral response of the photovoltaic modules enhanced in broadband range, which can improve the utilization efficiency of optical energy for the applications of sensing, imaging, optical communication, and energy harvesting.

In this study, we explore the potential of using a straightforward neural network inspired by the retina model to efficiently restore low-light images. The retina model imitates the neurophysiological principles and dynamics of various optical neurons. Our proposed neural network model reduces the computational overhead compared to traditional signal-processing models while achieving results similar to complex deep learning models from a subjective perceptual perspective. By directly simulating retinal neuron functionalities with neural networks, we not only avoid manual parameter optimization but also lay the groundwork for constructing artificial versions of specific neurobiological organizations.

Abstract: Image aesthetic assessment (IAA) with neural attention has made significant progress due to its effectiveness in object recognition. Current studies have shown that the features learned by convolutional neural networks (CNN) at different learning stages indicate meaningful information. The shallow feature contains the low-level information of images and the deep feature perceives the image semantics and themes. Inspired by this, we propose a visual enhancement network with feature fusion (FF-VEN). It consists of two sub-modules, the visual enhancement module (VE module) and the shallow and deep feature fusion module (SDFF module). The former uses an adaptive filter in the spatial domain to simulate human eyes according to the region of interest (ROI) extracted by neural feedback. The latter not only takes out the shallow feature and the deep feature by transverse connection, but also uses a feature fusion unit (FFU) to fuse the pooled features together with the aim of information contribution maximization. Experiments on standard AVA dataset and Photo.net dataset show the effectiveness of FF-VEN.

Deep-learning-based speech enhancement techniques have been recently grown in interest, since their impressive performance can potentially benefit a wide variety of digital voice communication systems. However, such performance has been evaluated mostly in offline audio processing scenarios (i.e. feeding the model, in one go, a complete audio recording, which may extend several seconds). It is of great interest to evaluate and characterize the current state-of-the-art in applications that process audio online (i.e. feeding the model a sequence of segments of audio data, concatenating the results at the output end). Although evaluations and comparisons between speech enhancement techniques have been carried out before, as far as the author knows, the work presented here is the first that evaluates the performance of such techniques in relation to their online applicability. Meaning, this work measures how the output signal-to-interference ratio (as a separation metric), the response time and memory usage (as online metrics) are impacted by the input length (the size of audio segments), in addition to the amount of noise, amount and number of interferences, and amount of reverberation. Three popular models were evaluated, given their availability on public repositories and online viability: MetricGAN+, Spectral Feature Mapping with Mimic Loss, and Demucs-Denoiser. The characterization was carried out using a systematic evaluation protocol based on the Speechbrain framework. Several intuitions are presented and discussed, and some recommendations for future work are proposed.

In recent years, neural networks based on attention mechanisms have been increasingly widely used in speech recognition, separation, enhancement, and other fields. In particular, the convolution-augmented transformer has achieved good performance as it can combine the advantages of convolution and self-attention. Recently, the gated attention unit (GAU) has been proposed. Compared with the traditional multi-head self-attention, approaches with GAU are effective and computationally efficient. In this article, we propose a network for speech enhancement called CGA-MGAN, a kind of Metric GAN based on convolution-augmented gated attention. CGA-MGAN captures local and global correlations in speech signals at the same time through the fusion of convolution and gated attention units. Experiments on Voice Bank + DEMAND show that the CGA-MGAN we propose achieves an excellent performance (3.47 PESQ, 0.96 STOI, and 11.09dB SSNR) at a relatively small model size (1.14M).

Vision loss can be avoided if diabetic retinopathy (DR) is diagnosed and treated promptly. Following are the main 5 DR stages: none, moderate, mild, proliferate, and severe. In this study, a deep learning (DL) model is presented that diagnoses all 5 stages of DR with more accuracy than previous methods. The suggested method presents two scenarios: case 1 with image enhancement using contrast limited adaptive histogram equalization (CLAHE) filtering algorithm in conjunction with an Enhanced Super-resolution generative adversarial network (ESRGAN), and case 2 without image enhancement; augmentation techniques are then performed to generate a balanced dataset utilizing the same parameters for both cases. Using Inception-V3 applied to the Asia Pacific Tele-Ophthalmology Society (APTOS) datasets, the developed model achieved an accuracy of 98.7% for case 1 and 80.87% for case 2, which is greater than existing methods for detecting the five stages of DR. It was demonstrated that using CLAHE and ESRGAN improves a model's performance and learning ability.

Holothuria scabra Jaeger 1833, known as sandfish visually, Its visible external body has a soft, flexible texture. Sandfish is included in the Echinodermata phylum and Holothuroidea class, which has an important ecological and economic role. This research proposes to decide the suitability site in an intermediate culture model of sea ranching harvest type based on ecological, socio-cultural and Karimunjawa National Park zoning plan. Data collected has done in March 2020, November 2020 and August 2021. The data analysed on the environmental suitability level was based on several essential criteria matrices used by ArcGIS 10.8.2. They were four classes performed (high suitable, suitable that is enough, suitable with conditionals, and not suitable) based on each variable and matrix classification from main factor (6 variables), supporting factor (5 variables), dan another factors (1 variable). The highest score was 35, and the lowest was 23 during the class interval value. The analysis showed that the aquatic environment that was High Suitable (S1) for sandfish life was Gede Lagoon. It has been determined to be highly suitable for developing sandfish cultivation. Furthermore, the Sea Ranching Harvesting Type development would recommend being carried out in waters that do not have limiting factors.

The study of the influence of the nanoparticle volume fraction and aspect ratio of microchannels on the fluid flow and heat transfer characteristics of nanofluids in microchannels is important in the optimal design of heat dissipation systems with high heat flux. In this work, the computational fluid dynamics method was adopted to simulate the flow and heat transfer characteristics of two types of water–Al2O3 nanofluids with two different volume fractions and five types of microchannel heat sinks with different aspect ratios. Results showed that increasing the nanoparticle volume fraction reduced the average temperature of the liquid–solid heat transfer surface and thereby improved the heat transfer capacity of the nanofluids. Meanwhile, the increase of the nanoparticle volume fraction led to a considerable increase in the pumping power of the system. Changing the aspect ratio of the microchannel effectively improved the heat transfer capacity of the heat sink. Moreover, increasing the aspect ratio effectively reduced the average temperature of the heating surface of the heat sink without significantly increasing the flow resistance loss. When the aspect ratio exceeded 30, the heat transfer coefficient did not increase with the increase of the aspect ratio. The results of this work may offer guiding significance for the optimal design of high heat flux microchannel heat sinks.

The composition of bacteria in the gastrointestinal tract of piglets is easily affected by environmental changes, particularly during the weaning period. Compound strains of Lactobacillus reuteri and Lactobacillus salivarius were supplemented to piglets during pre- and post-weaning to determine their effects in improving the growth performance and ameliorating the diarrhea rate and stress caused by antioxidation in piglets. A larger number of L. reuteri and L. salivarius colonized the distal segment of the ileum and the total numbers of Lactobacillus spp. and Bifidobacterium were higher in the ileal mucous membrane and cecal lumen with probiotics supplementation. The numbers of antioxidative and immune molecules were increased in the plasma following compound bacteria (CL) supplementation, whereas cortisol and endotoxin levels were lower and growth hormone and insulin-like growth factor 1 were higher. Spearman’s and KEGG analysis of the bacterial operational taxonomic unit and antioxidative and immune indices and metabolic genes indicated that the body growth modulation by CL supplementation could be attributed to optimization of the intestinal bacterial composition. Collectively, these results suggest that supplementation with CL could reduce stress and improve the growth performance of piglets during weaning by optimizing the intestinal bacterial composition.

Increased traffic in combination with growing environmental impacts, have led to accelerated degradation of the built infrastructure. In reinforced concrete structures, the corrosion of steel reinforcement is the predominant cause of deterioration. Thus, over the last years the use of glass fiber reinforced polymer (GFRP) composites as internal reinforcement bars (rebars) for concrete structures was evaluated, and has been proved to be a viable alternative to traditional steel reinforcement mainly due to its tensile strength and non-corrosive nature. However, thus far, the GFRP rebar market is diverse and manufacturers around the world produce GFRP rebar types with different surface enhancement to improve the bond to concrete characteristics. In this study, the bond performance of three dissimilar GFRP rebar types (sand coated, helically grooved and with surface lugs) was evaluated over time in seawater environments, with a focus on the bond strength. Accordingly, specimens were expose to seawater in circulating chambers, at three different temperatures (23 °C, 40 °C and 60 °C) for multiple time periods (60 and 120 days). To evaluate the bond performance, pullout tests were conducted according to ASTM D7913 [1]. The results showed that the bond strength varies with surface enhancement features. However, the bond strength didn’t vary significantly with exposure time and temperature for all three evaluated rebar types.

One of the hallmarks of Alzheimer’s disease (AD) is the accumulation of beta-amyloid peptide (Aβ) leading to formation of soluble neurotoxic Aβ oligomers and insoluble amyloid plaques in various parts of the brain. Aβ undergoes post-translational modifications that alter its pathogenic properties. Aβ is produced not only in brain, but also in the peripheral tissues. Such Aβ, including its post-translationally modified forms, can enter the brain from circulation by binding to RAGE and contribute to the pathology of AD. However, the transport of modified forms of Aβ across the blood–brain barrier (BBB) has not been investigated. Here, we used a transwell BBB model as a controlled environment for permeability studies. We found that Aβ42 containing isomerized Asp7 residue (iso-Aβ42) and Aβ42 containing phosphorylated Ser8 residue crossed the BBB better than unmodified Aβ42, which correlated with different contribution of endocytosis mechanisms to the transport of these isoforms. Using microscale thermophoresis, we observed that RAGE binds to iso-Aβ42 an order of magnitude weaker than to Aβ42. Thus, post-translational modifications of Aβ increase the rate of its transport across the BBB and modify the mechanisms of the transport, which may be important for AD pathology and treatment.

CD44 is a cell surface glycoprotein, which is widely expressed on normal and cancer cells. CD44 is involved in cell adhesion, migration, proliferation, survival, stemness, and chemo-resistance. Therefore, CD44 is thought to be a promising target for cancer diagnosis and therapy. In this study, we established anti-CD44 monoclonal antibodies (mAbs) by immunizing mice with CD44v3-10 ectodomain and screening using enzyme-linked immunosorbent assay. We then characterized them using flow cytometry, western blotting, and immunohistochemistry. One of the established clones (C44Mab-46; IgG1, kappa) reacted with CD44s-overexpressed Chinese hamster ovary-K1 cells (CHO/CD44s) or esophageal squamous cell carcinoma (ESCC) cell lines (KYSE70 and KYSE770). The KD of C44Mab-46 for CHO/CD44s, KYSE70, and KYSE770 was 1.1×10-8 M, 4.9×10-8 M, and 4.1×10-8 M, respectively. C44Mab-46 detected CD44s of CHO/CD44s and KYSE70, and CD44v of KYSE770 in western blot analysis. Furthermore, C44Mab-46 strongly stained esophageal squamous carcinoma cells in immunohistochemistry using formalin-fixed paraffin-embedded ESCC tissues. Taken together, C44Mab-46 is very useful for detecting CD44 in various applications.

Immunohistochemistry is a widely used technique for research and diagnostic purposes that relies on the recognition by antibodies of antigens expressed in tissues. However, tissue processing and particularly formalin fixation affect the conformation of these antigens through the formation of methylene bridges. Although antigen retrieval techniques can partially restore antigen immunoreactivity, it is difficult to identify antibodies that can recognize their target especially in formalin-fixed paraffin-embedded tissues. Most of the antibodies currently used in immunohistochemistry have been obtained by animal immunization; however, in vitro display techniques represent alternative strategies that have not been fully explored yet. This review provides an overview of phage display-based antibody selections using naïve antibody libraries on various supports (fixed cells, dissociated tissues, tissue fragments, and tissue sections) that have led to the identification of antibodies suitable for immunohistochemistry.

(1) Background: Hepatitis C virus (HCV) screening mostly uses a one-assay anti-HCV testing approach, which has a higher probability of false-positive results in populations with low HCV prevalence. (2) Methods: In this investigation, 17,926 participants, were screened for HCV, and the reactives were tested using a two-assay anti-HCV approach: Elecsys ElectroChemiLuminescence (ECL) and a ChemiLuminescence ImmunoAssay (CLIA), respectively. A recombinant immunoblot assay (RIBA) was performed to confirm anti-HCV positivity. Statistical analysis was performed. (3) Results: A total of 350 specimens resulted reactive in the ECL screening, of which CLIA retesting showed that 292 (83.4%) were anti-HCV reactive (283 positive, 9 indeterminate, none negative by RIBA), but 58 (16.6%) were not anti-HCV reactive (15 positive, 12 indeterminate, 31 negative by RIBA). The two-assay strategy significantly improved the positive predictive value (PPV: 95.00%) with χ2: 7.59(p&lt;0.01) then the PPV assessed by one assay (PPV: 90.6%) with χ2: 34.51 (p&lt; 0.001). The ROC curve defined a sensibility and specificity for the dual approach of: 99.66% and 100.00%. (4) Conclusions: Compared with a one-assay testing strategy, the two-assay testing strategy may significantly reduce false positives in anti-HCV testing and identify inactive HCV infection in low seroprevalence populations.

Magneto-electrochemistry (MEC) is a unique paradigm in science, where electrochemical experiments are carried out as a function of an applied magnetic field, creating a new horizon of potential scientific and technological applications. Over the time, detailed understanding of this research domain was developed to identify and rationalize the possible effects exerted by a magnetic field on the various microscopic processes occurring in an electrochemical system, such as: electrolyte properties governed by charge-transfer process (electric conductivity, viscosity, and diffusivity), mass transfer, electrochemical kinetics and on the structure/quality of products formed either at the working electrode or in the electrochemical cell. Particularly, magnetic field controlled chiral architecture obtained from deposited metal, alloys and catalyst and their excellent enantio-recognition in experimental frame is highly appealing. Interestingly, Hall effect was also demonstrated in electrolytic medium via an impressive experimental technique which is being employed for further theoretical understanding in the field of magneto-electrochemical science. Later, a highly reproducible local temperature variation was observed in electrochemical electrolytes exposed to perpendicular magnetic and electric fields. However, until recent studies, none of the above mentioned reports considered the possibility of a spin-dependent related charge-transfer process. Recent experimental and theoretical studies reveal that electron’s transmission through chiral molecules is spin-selective and this effect has been referred to as chiral-induced spin-selectivity (CISS) effect. The CISS effect pave the way for the building up of a system characterized by a net magnetic moment exploiting the spin-filtering ability of chiral molecules. This interplay between chirality and magnetism may shed light on fundamental scientific aspects underlying the enantio-recognition and highly efficient electron-transfer that occurs in biological process.

Thalassemia is a heterogeneous congenital hemoglobinopathy common in the Mediterranean region, Middle East, Indian subcontinent, and Southeast Asia with increasing incidence in Northern Europe and North America due to immigration. Iron overloading is one of the major long-term complications in patients with thalassemia and can lead to organ damage and carcin-ogenesis. Hepatocellular carcinoma (HCC) is one of the most common malignancies in both transfusion-dependent thalassemia (TDT) and non-transfusion-dependent thalassemia (NTDT). The incidence of HCC in patients with thalassemia has increased over time, as better chelation therapy confers a sufficiently long lifespan for the development of HCC. The mechanisms of iron overloading-associated HCC development include the increased　reactive oxygen species (ROS), inflammation cytokines, dysregulated hepcidin, and ferroportin metabolism. The treat-ment of HCC in patients with thalassemia was basically similar to those in general population. However, due to the younger age of HCC onset in thalassemia, regular surveillance for HCC development is mandatory in TDT and NTDT. Other supplemental therapy and experience of novel treatment for HCC in thalassemia population were also reviewed in this article.

FMD is a highly contagious animal disease that occurs in cloven-hoofed animals including pigs. To prevent FMD, vaccines and adjuvants are used to induce an immune response, but it is not sufficient to show the effect of preventing viral infection. In this study, we conducted to evaluate the increasing effect of FMD vaccine SP antibody by administrating Zn-ASP to 100 pigs from three test pig farms with feed. FMD vaccine antibody titer and immunological index were analyzed using an enzyme-linked immunosorbent assay (ELISA) kit, and hematological and blood biochemical parameters were analyzed using an automatic blood analyzer. The titer of FMD vaccine SP antibody in the 0.2% Zn-ASP-administered group significantly increased compared to that in the positive control group only injected with FMD vaccine at 4 weeks after the first vaccination and at 4, 8 and 16 weeks after the second vaccination, respectively (p&lt;0.05). The FMD vaccine SP antibody positive rate was 100% until shipment. IFN-γ and IgA were significantly increased by Zn-ASP administration 4 weeks after the first vaccination and 4 weeks after the second vaccination (p&lt;0.05). On the other hand, serum AST, and CPK (p&lt;0.001) were significantly decreased by Zn-ASP. Our results show that the administration of Zn-ASP is effective in enhancing the antibody titer and immunity of the FMD vaccine by FMD vaccination, and it is thought that it can be used as an oral adjuvant (OrAd) to prevent viral diseases such as FMD.

The importance of antibodies in health care and the biotechnology research and development demands not only knowledge of their experimental structures at high resolution, but also practical implementation of this knowledge for both effective and efficient design and production of antibody for its use in both medical and research applications. While the experimental wet-lab approach is usually costly, laborious and time-consuming, computational (dry-lab) approaches, in spite of their intrinsic limitations in comparison with its experimental (wet-lab) counterpart, provide a cheaper and faster alternative option. For the first time, this article reports a comprehensive set of structural electrostatic features extracted from experimentally determined antigen-antibody-related structures, including especially those structural electrostatic features at the interfaces of all experimentally determined antigen-antibody complex structures as of February 29, 2020, to facilitate effective and efficient machine learning-based computational antibody design using currently available experimental structures inside Protein Data Bank.

The realm of natural language processing has always been fascinated by the intricacies of sentence semantics. The emergence of context-aware word representations, especially from pre-trained models like ELMO and BERT, has revolutionized several semantic tasks including but not limited to, question answering, text categorization, and sentiment analysis. Despite these advancements, the integration of supplementary knowledge, particularly syntactic, to augment semantic comprehension in models remains an area ripe for exploration. This paper introduces the Syntactic Enhancement Network (SEN), a pioneering method for synergizing syntactic elements with established pre-trained language models. Our approach encompasses a dual-phase evaluation: initially, we delve into the syntactic augmentation of both RNN-based and Transformer-based language models; subsequently, we test our SEN's proficiency in two specific domains: the task of sentence completion and the extraction of biological relationships. The results are striking, with SEN achieving a stellar 91.2% accuracy in sentence completion—surpassing baseline models by a substantial 37.8%. In the context of biological relation extraction, SEN demonstrates competitive prowess with a 75.1% F1 score.

This paper presents an approach to enhancing the clarity and intelligibility of speech in digital communications compromised by various background noises. Utilizing deep learning techniques, specifically a Variational Autoencoder (VAE) with 2D convolutional filters, we aim to suppress background noise in audio signals. Our method focuses on four simulated environmental noise scenarios: storms, wind, traffic, and aircraft. Training dataset has been obtained from public sources (TED-LIUM 3 dataset, which includes audio recordings from the popular TED-TALK series) combining with these background noises. The audio signals were transformed into 2D power spectrograms, upon which our VAE model was trained to filter out the noise and reconstruct clean audio. Our results demonstrate that the model outperforms existing state-of-the-art solutions in noise sup-pression. Although differences in noise types were observed, it was challenging to definitively conclude which background noise most adversely affects speech quality. Results have been assessed with objective methods (mathematical metrics) and subjective (listening to a set of audios by humans). Notably, wind noise showed the smallest deviation between the noisy and cleaned audio, perceived subjectively as the most improved scenario. Future work involves refining the phase calculation of the cleaned audio and creating a more balanced dataset to minimize differences in audio quality across scenarios. Additionally, practical ap-plications of the model in real-time streaming audio are envisaged. This research contributes significantly to the field of audio signal processing by offering a deep learning solution tailored to various noise conditions, enhancing digital communication quality.

With increasing demand from unmanned driving and robotics, more attention has been paid to point cloud-based 3D object accurate detection technology. However, due to the sparseness and irregularity of the point cloud, the most critical problem is how to utilize the relevant features more efficiently. In this paper, we proposed a point-based object detection enhancement network to improve the detection accuracy in the 3D scenes understanding based on the distance features. Firstly, the distance features are extracted from the raw point sets and fused with the raw features about reflectivity of the point cloud to maximizing the use of information in point cloud. Secondly, we enhanced the distance features and raw features that we collectively refer to them as self-features of the key points in Set Abstraction (SA) layers with the self-attention mechanism, so that the foreground points can be better distinguished from the background points. Finally, we revised the group aggregation module in SA layers to enhance the feature aggregation effect of key points. We conducted experiments on the KITTI dataset and nuScenes dataset and the results show the enhancement method proposed in this paper has excellent performance.

Recently, deep learning-based image quality enhancement models have been proposed to improve the perceptual quality of distorted synthesized views impaired by compression and Depth Image Based Rendering (DIBR) process in multiview video systems. However, due to the lack of multi-view video plus depth data, the training data for quality enhancement models is small, which limits the performance and progress of these models. Augmenting the training data to enhance the Synthesized View Quality Enhancement (SVQE) models is a feasible solution. In this paper, we suggest a deep learning-based SVQE model using more synthetic Synthesized View Images (SVIs). To simulate the irregular geometric displacement of DIBR distortion, a random irregular polygon-based SVI synthesis method is proposed based on existing massive RGB/RGBD data, and a synthetic synthesized view database is constructed, which includes synthetic SVIs and DIBR distortion masks. Moreover, to further guide the SVQE models to focus more precisely on DIBR distortion, the DIBR distortion mask prediction network which could predict the position and variance of DIBR distortion is embedded into the SVQE models. The experimental results demonstrate that by pretraining on the synthetic SVI database, the performance of the existing SVQE models could be greatly promoted. In addition, by introducing the DIBR distortion mask prediction network, the SVI quality could be further enhanced.

Self-enhancement (SE) is often overlooked as a fundamental cognitive ability mediated via the Pre-Frontal Cortex (PFC). Here we present research that establishes the relationship between the PFC, SE, and the potential evolved beneficial mechanisms. Specifically, we believe there is now enough evidence to speculate that SE exists to provide significant benefits and should be considered a normal aspect of the self. Whatever the metabolic or social cost, the upside of SE is great enough that it is a core and fundamental psychological construct. Furthermore, though entirely theoretical, we suggest that a critical reason the PFC has evolved so significantly in Homo sapien is to, in part, sustain SE. We therefore elaborate as to its proximate and ultimate mechanisms.

The temperature-assisted laser shock process has shown promising prospects in the fields of forming manufacturing and surface strengthening. However, large-scale application of this process is limited by the instability and failure of confinement medium at high temperatures (≥300 ℃). Aiming at this problem, we propose a novel laser shock strategy based on Leidenfrost effect, where the suspended droplets are utilized as the confinement medium. According to the sequence of images acquired by time delay system and high-speed camera, the droplet dynamics behavior is studied. The focusing enhancement effect of the droplet is comprehensively explored. And the correlations between droplet size, ambient temperature, vapor layer thickness and focusing effect are investigated. Combining the dynamics and focusing enhancement effect of droplets, a theoretical model of laser shock pressure under droplet confinement is established. Finally, the effectiveness and feasibility of the droplet-based laser shock strategy in high temperature processing environments are verified by typical applications in laser shock forming and laser shock peening fields. The results show that the droplet-based laser shock process presents better forming effect. And the mechanical property tests demonstrate that this process can obtain the simultaneous improvement of the strength (~51%) and ductility (~6.4%) of annealed Cu. The multiscale plasticity mechanisms of the strengthened material are comprehensively investigated. We believe that this low-energy, low-cost and high-quality process can provide a new solution for the industrial application of laser shock at high temperatures.

Human beatboxing is a vocal art making use of speech organs to produce vocal drum sounds and imitate musical instruments. Beatbox sound classification is a current challenge that can be used for automatic database annotation and music-information retrieval. In this study, a large-vocabulary humanbeatbox sound recognition system was developed with an adaptation of Kaldi toolbox, a widely-used tool for automatic speech recognition. The corpus consisted of eighty boxemes, which were recorded repeatedly by two beatboxers. The sounds were annotated and transcribed to the system by means of a beatbox specific morphographic writing system (Vocal Grammatics). The image processing techniques plays vital role on image Acquisition, image pre-processing, Clustering, Segmentation and Classification techniques with different kind of images such as Fruits, Medical, Vehicle and Digital text images etc. In this study the various images to remove unwanted noise and performs enhancement techniques such as contrast limited adaptive histogram equalization, Laplacian and Harr filtering, unsharp masking, sharpening, high boost filtering and color models then the Clustering algorithms are useful for data logically and extract pattern analysis, grouping, decision-making, and machine-learning techniques and Segment the regions using binary, K-means and OTSU segmentation algorithm. It Classifying the images with the help of SVM and K-Nearest Neighbour(KNN) Classifier to produce good results for those images.

In research applications across several areas, noise removal is indispensable for accuracy of final results. Noise is caused due to physical principals, such as background electronic noise, quantum effect, and wave rebound effect to name a few. Noise removal can help improve results in medical, astronomy, defense, and numerous other fields. Addressing this limitation would result in potentially low cost, automatic, and reliable systems. In this paper, a generalized new approach i.e. Multi-Frame Noise Removal (MFNR) is proposed for noise removal. Given any type of data, the probability density function (PDF) of the noise can be determined. Herein, we extracted the noise PDF parameters using KDE (Kernel Density Estimation). Because the data is corrupted by “deterministic” noise, hence can be cleaned. This could be used as a general purpose noise removal tool. The data point with same position in multiple frames helps us determine the noise PDF characteristics and hence making it possible to remove noise. The conventional wisdom which states that noise removal and detail preservation are contrary to each other is not true for MFNR. Experimental results validate our proposed method which showed practically complete noise reduction based on number of frames used, as compared to existing benchmark methods.

This study aims to investigate the Stratosphere-Troposphere Exchange (STE) events and ozone trends over Irene (25.5°S, 28.1°E). Twelve years of ozonesondes data (2000–2007, 2012–2015) from Irene station operating in the framework of the Southern Hemisphere Additional Ozonesodes (SHADOZ) was used to study the troposphere (0–16 km) and stratosphere (17– 28 km) ozone (O₃) vertical profiles. Ozone profiles were grouped into three categories (2000–2003, 2004–2007 and 2012–2015) and average composites were calculated for each category. Fifteen O₃ enhancement events were identified over the study period. These events were observed in all seasons (one event in summer, four events in autumn, five events in winter and five events in spring), however, they predominantly occur in winter and spring. The STE events presented here are observed to be influenced by the Southern Hemisphere polar vortex. During the STE events, the advected potential vorticity maps assimilated using Modélisation Isentrope du transport Méso–échelle de l’Ozone Stratosphérique par Advection (MIMOSA) model for the 350 K (~12–13 km) isentropic level indicated a transport of high latitude air masses which seems to be responsible for the reduction of the O₃ mole fractions at the lower stratosphere over Irene which takes place at the same time with the enhancement of ozone in the upper troposphere. In general, the stratosphere is dominated by higher Modern Retrospective Analysis for Research Application (MERRA-2) potential vorticity (PV) values compared to the troposphere. However, during the STE events, higher PV values from the stratosphere were observed to intrude the troposphere. Ozone decline was observed from 12 km to 24 km with highest decline occurring from 14 km to 18 km. An average decrease of 6.0 and 9.1% was calculated from 12 to 24 km in 2004–2007 and 2012–2015 respectively. The observed decline occurred in the upper troposphere and lower stratosphere with winter and spring showing more decline compared with summer and autumn.

The potential of Sorghum bicolor L. (Moench) (Epuripur 1995) to phytoremediate petroleum oil-adulterated soils from an automobile repair workshop and the effect of enhancement factors: NPK fertilizer, cow dung and sewage sludge in in situ phytoremediation of the soil by the plant were assessed in this study. 50kg of petroleum oil-contaminated soil was collected from the workshop and divided into five equal portions. Four portions were potted with four sorghum plants with three subjected to equal amounts of enhancements (5%w/w) under normal growth conditions for 72 days. Representative soil samples were collected from spots at depths of 0–10 cm and 10–20 cm from the potted soils and subjected to Soxhlet oil extraction after 72 days. Experimental results revealed that S. bicolor survived in the petroleum oil-contaminated soils. Amendment of the petroleum oil-vitiated soils with cow dung, sewage sludge and NPK fertilizer augmented the remediation capacity of Epuripur 1995 by 12.5%, 6.3% and 9.1%. Addition of cow dung to crude oil contaminated soils could make such soils fully reestablished for agricultural activities. Further research aimed at determination of the phytoremediation potential of cereals such as corn, barley, rye, millet should be done.

The notion of enhancement of the image is to ameliorate the perceptibility of information contained in an image. In the present research, a novel technique for the enhancement of image quality is propounded using fuzzy logic technique with a cuckoo optimization algorithm. Generally, the image is transformed from RGB domain to HSV domain keeping the color information intact within the image. The image has been categorized into three regions: underexposed, overexposed and mixed region on the basis of two threshold values. For the fuzzification of under and overexposed area the degree of membership is defined by the Gaussian membership, while the mixed area is fuzzified by parametric sigmoid function. The key parameters like visual factors and fuzzy contrast provide the quantitative analysis of an image. An objective function is framed which involves entropy and visual factor has been optimized by a new evolutionary cuckoo optimization algorithm. The results procured after simulation by the cuckoo optimization algorithm are compared with Bacterial foraging algorithm and ant colony optimization based image enhancement and this approach is found to be improved.

Antibody-drug conjugates (ADCs), a groundbreaking advancement in cancer therapy, synergistically combine the precision of monoclonal antibodies with the potent destruction capabilities of cytotoxic drugs, signifying a new era in the targeted oncological treatments. This comprehensive paper delves into the evolving field of antibody-drug conjugates (ADCs) and their pivotal role in cancer therapy. We have conducted an in-depth exploration of the structural components of ADCs, including target antigens, monoclonal antibodies, chemical linkers, and cytotoxic payloads, each playing a crucial role in determining the efficacy and safety profile of these novel therapies. A detailed market analysis reveals the leading pharmaceutical companies shaping the ADC landscape, reflecting the growing interest and potential in this therapeutic approach. We further dissect the engineering intricacies of ADCs, focusing on their ability to target specific cancer cell antigens while minimizing off-target effects, thus offering a more focused treatment with reduced systemic side effects compared to traditional chemotherapy. This approach holds promise in a heightened therapeutic index and decreased toxicity. The mechanisms and effector functions of ADCs are explored, highlight- ing their multifaceted strategy in combating cancer. We include a comprehensive look at how ADCs operate from initial blood circulation to the induction of apoptosis in cancer cells. We also review several key ADCs currently in use or under investigation, offering insights into their unique mechanisms of action, pharmacokinetics, and clinical implications. The discussion extends to drug creation modalities, focusing on innovative conjugation techniques that enhance ADC homogeneity and therapeutic efficacy. In conclusion, the paper underscores the transformative potential of ADCs in the realm of cancer treatment, marking a shift towards more precise and targeted therapeutic approaches. By offering a thorough analysis of ADC technology, this paper sheds light on the prospects of these groundbreaking therapies in the ongoing fight against cancer.

C-X-C motif chemokine receptor 3 (CXCR3, CD183) is a G-protein-coupled receptor for CXCL9, CXCL10, and CXCL11. CXCR3 signaling induces chemotaxis of immune cells to inflammation sites and promotes inflammation in inflammatory diseases. Various mouse models to mimic the pathogenesis of each disease have been developed to understand mechanisms and evaluate therapeutics for these diseases. Although CXCR3 is an attractive target to suppress inflammation, anti-CXCR3 therapeutic agents have not been approved. In this study, we established a novel anti-mouse CXCR3 (mCXCR3) monoclonal antibody, Cx₃Mab-4 (rat IgG₁, kappa), using the Cell-Based Immunization and Screening method. Flow cytometric analysis demonstrated that Cx₃Mab-4 bound to mCXCR3-overexpressed Chinese hamster ovary-K1 (CHO/mCXCR3) cells, but did not react to parental CHO-K1 cells. The dissociation constant of Cx₃Mab-4 was determined as 1.3 × 10^-9 M, indicating that Cx₃Mab-4 possesses a high affinity to mCXCR3-expressing cells. Cx₃Mab-4 could be useful for targeting CXCR3-expressing cells in preclinical mouse models.

The C-X-C motif chemokine receptor-1 (CXCR1) is a rhodopsin-like G-protein-coupled receptor, expressed on the cell surface of immune cells and tumors. CXCR1 interacts with some C-X-C chemokines, such as CXCL6, CXCL7, and CXCL8/interleukin-8, which are produced by various cells. Since CXCR1 is involved in several diseases including tumors and diabetes mellitus, drugs targeting CXCR1 has been developed. Therefore, the development of sensitive monoclonal antibodies (mAbs) for CXCR1 has been desired for the diagnosis and treatment. This study established a novel anti-mouse CXCR1 (mCXCR1) mAb; Cx₁Mab-1 (rat IgG₁, kappa), using the Cell-Based Immunization and Screening (CBIS) method. Cx₁Mab-1 reacted with mCXCR1-overexpressed Chinese hamster ovary-K1 (CHO/mCXCR1) and mCXCR1-overexpressed LN229 glioblastoma (LN229/mCXCR1) in flow cytometry. Cx₁Mab-1 demonstrated a high binding affinity for CHO/mCXCR1 and LN229/mCXCR1 with a dissociation constant of 2.6×10^-9 M and 2.1×10^-8 M, respectively. Furthermore, Cx₁Mab-1 could detect mCXCR1 by western blot analysis. These results indicated that Cx₁Mab-1 is useful for detecting mCXCR1, and provides a possibility for targeting mCXCR1-expressing cells in vivo experiments.

The performance of the nanoribbon biosensor upon the use of two different types of molecular probes — the antibodies and the aptamers against HCVcoreAg — has been tested. The sensor chips employed are based on “silicon-on-insulator structures”. Two different HCVcoreAg preparations have been tested: recombinant b-galactosidase-conjugated HCVcoreAg (“Virogen”, USA) and recombinant HCVcoreAg (“Vector-Best”, Russia). Upon the detection of either type of the antigen preparation, the lowest concentration of the antigen detectable in buffer with pH 5.1 has been found to be approximately equal, amounting to ~10^–14 M. This value has been found to be similar upon the use of either type of molecular probes.

Antibody-drug conjugates (ADCs) have provided new therapeutic options and significant promise for patients with cancers, particularly where existing treatments are limited. Substantial effort in ADC development is underway globally, with 13 ADCs currently approved and many more in development [1]. Therapeutic benefits of ADCs leverage the ability to selectively target cancer cells through antibody binding, resultant relative sparing of non-malignant tissues, and the targeted delivery of a cytotoxic payload. Consequently, this drug class has demonstrated activity in multiple malignancies refractory to standard therapeutic options [1-4]. Despite this, limitations exist, including narrow therapeutic windows, unique toxicity profiles, development of therapeutic resistance, and appropriate biomarker selection [5-7]. This review will describe the development of ADCs, their mechanisms of action, pivotal trials, and approved indications and identify common themes. Current challenges and opportunities will be discussed for this drug class in cancer therapeutics at a time when significant developments in antibody therapies, immunotherapy and targeted agents are occurring.

Cluster of differentiation 44 (CD44) is a type I transmembrane glycoprotein, and has been shown as a cell surface marker of cancer stem-like cells in various cancers. Especially, the splicing variants of CD44 (CD44v) are overexpressed in cancers, and play critical roles in cancer stemness, invasiveness, and resistance to chemotherapy and radiotherapy. Therefore, the understanding of the function of each CD44v is indispensable for the CD44-targeting therapy. CD44v9 contains the variant 9-encoded region, and its expression predicts poor prognosis in patients with various cancers. CD44v9 plays critical roles in the malignant progression of tumors. Therefore, CD44v9 is a promising target for cancer diagnosis and therapy. Here, we developed sensitive and specific monoclonal antibodies (mAbs) against CD44 by immunizing mice with CD44v3–10-overexpressed Chinese hamster ovary CHO-K1 (CHO/CD44v3–10) cells. We first determined their critical epitopes using enzyme-linked immunosorbent assay, and characterize their applications to flow cytometry, western blotting, and immunohistochemistry. One of the established clones, C₄₄Mab-1 (IgG₁, kappa) reacted with a peptide of the variant 9-encoded region, indicating that C₄₄Mab-1 recognizes CD44v9. C₄₄Mab-1 reacted with CHO/CD44v3–10 cells or colorectal cancer cell lines (COLO201 and COLO205) by flow cytometry. The apparent dissociation constant (K_D) of C₄₄Mab-1 for CHO/CD44v3–10, COLO201, and COLO205 was 2.5 × 10⁻⁸ M, 3.3 × 10⁻⁸ M, and 6.5 × 10⁻⁸ M, respectively. Furthermore, C₄₄Mab-1 was able to detect the CD44v3–10 in western blotting, and endogenous CD44v9 in immunohistochemistry using colorectal cancer tissues. These results indicated that C₄₄Mab-1 is useful for detecting CD44v9 not only in flow cytometry or western blotting but also in immunohistochemistry against colorectal cancers.

CD44 is a cell surface glycoprotein, and its isoforms are produced by the alternative splicing with the standard and variant exons. The CD44 variant exon containing isoforms (CD44v) are overexpressed in carcinomas. CD44v6 is one of the CD44v, and its overexpression predicts poor prognosis in colorectal cancer (CRC) patients. CD44v6 plays critical roles in CRC adhesion, proliferation, stemness, invasiveness, and chemoresistance. Therefore, CD44v6 is a promising target for cancer diagnosis and therapy for CRC. In this study, we established anti-CD44 monoclonal antibodies (mAbs) by immunizing mice with CD44v3-10-overexpressed Chinese hamster ovary-K1 (CHO) cells. We then characterized them using enzyme-linked immunosorbent assay, flow cytometry, western blotting, and immunohistochemistry. One of the established clones (C44Mab-9; IgG1, kappa) reacted with a peptide of variant 6-encoded region, indicating that C44Mab-9 recognizes CD44v6. Furthermore, C44Mab-9 reacted with CHO/CD44v3-10 cells or CRC cell lines (COLO201 and COLO205) by flow cytometry. The apparent KD of C44Mab-9 for CHO/CD44v3-10, COLO201, and COLO205 was 8.1 × 10−9 M, 1.7 × 10−8 M, and 2.3 × 10−8 M, respectively. C44Mab-9 detected the CD44v3-10 in western blotting, and partially stained the formalin-fixed paraffin-embedded CRC tissues in immunohistochemistry. Collectively, C44Mab-9 is useful for detecting CD44v6 in various applications.

Objective: This study aimed to evaluate the antibody responses in two adult age groups after diphtheria vaccination. Study Design: An observational analytic study was carried out to determine the difference in serum titer of anti-diphtheria antibody. Methods: Serum antibody titers were measured just before and 3 months after injection of Diphtheria toxoid vaccine. Vaccine was given to two adult age groups of health care personnel in hospital: the young (< 40 years) and the middle-aged (≥ 40 years). Data were analyzed using the Mann-Whitney test (p < 0.05). Results: Significant increase in serum anti-diphtheria antibody titers were recorded after vaccination in both age group (p < 0.001 in young adult and p = 0.001 in middle-aged adult, respectively). There were no substantial differences between the two groups in terms of antibody titer before vaccination (p = 0.741), 3 months after vaccination (p = 0.317) and in the increase of antibody titer (p = 0.479). Conclusions: This study showed that there was no significant difference in the increase of anti-diphtheria antibody titers between the two age groups, proving that both young and middle-aged adults had an equal immune response to a given diphtheria vaccine.

Chikungunya virus (CHIKV) is an alphavirus that causes febrile illness punctuated by severe polyarthralgia. After the emergence of CHIKV in the Western Hemisphere, multiple reports of congenital infections were published that documented neurological complications, cardiac defects, respiratory distress, and miscarriage. The Western Hemisphere is endemic to several alphaviruses and whether antigenic cross-reactivity can impact the course of infection has not been explored. Recent advances in biomedical engineering have produced cell co-culture models that replicate the cellular interface at the maternal fetal axis. We employed a trans-well assay to determine if cross-reactive antibodies affected the movement and replication of CHIKV across placental cells and into an embryoid body. The data show that antibodies to Venezuelan equine encephalitis virus (VEEV) significantly reduced CHIKV viral load in embryoid bodies. The data highlight that viral pathogenesis can be cell-specific and that exploiting antigenic cross-reactivity could be an avenue for reducing the impact of congenital CHIKV infections.

Ionic channels are present in eucaryotic plasmatic and intracellular membranes. They coordinate and control several functions. One of the most diverse ionic channels family are the potassium (K) channels. Within this family are the ATP-dependent potassium channels (KATP), which belong to the potassium rectifier channel family. These channels were initially described in heart muscle, yet they are also present in different types of tissues such as pancreatic, skeletal muscle, brain, and vascular and non-vascular smooth muscle. In ß-pancreatic cells, KATP are primarily responsible for maintaining membrane potential and for the depolarization mediated insulin release. KATP density/activity seems to be determinant in physiological the outcome, in pancreatic cells decrease of this density/activity may be related to Insulin resistance (IR). In extra pancreatic tissues KATP relation with IR is beginning to be explored. It is possible that in skeletal muscle, the KATP are involved in insulin dependent glucose recapture and that KATP activation leads to IR. In adipose tissue, KATP containing Kir6.2, could be related to increase in free fatty acids and insulin resistance, therefore, pathological processes leading to a prolonged adipocyte KATP inhibition might promote obesity related to insulin resistance. In central nervous system KATP activation can regulate peripheric glycemia and lead to brain IR which could be a much earlier manifestation of peripheral alterations that lead to the development of pathologies such as obesity and type 2 diabetes mellitus. In this review we aim to discuss the KATP channel characteristics, its relationship to known clinical disorders and the mechanisms and potential relations with peripheral and central insulin resistance.

A theoretical nonlocal thermoelastic model for studying the effects of the thermal conductivity variability on a rotating nanobeam has been described in the present article. The theory of thermal stress is employed using the Euler–Bernoulli beam model and generalized heat conduction with phase lags. It is believed that the thermal conductivity of the current model varies linearly according to temperature. Due to variable harmonic heat, the considered nanobeam excited and was subjected to a time-varying exponential decay load. Using the Laplace transform process, the analytical solutions for displacement, deflection, thermodynamic temperature and bending moment of rotating nanobeams are provided in final forms and a numerical example has been taken to address the problem. A comparison of the stated results was displayed and additionally, the influences of non-local parameters and varying load were analyzed and examined. We also investigate how the linear changes in the temperature of physical properties can influence both the static and dynamic responses to the rotating nanobeam.

Results are presented concerning the influence on the water splitting process of enantiopure tartaric acid present in bulk solution. Stainless steel and electrodeposited nickel are used as working electrode (WE) surface. The latter is obtained by electrodeposition on the two poles of a magnet. The influence and role played by the chiral compound in solution has been assessed by comparing the current values, in cyclic voltammetry (CV) experiments, recorded in the potential range at which oxygen evolution reaction (OER) occurs. In the case of tartaric acid and nickel WE a spin polarization of about 4 % is found. The use of the chiral environment (bulk solution) and ferromagnetic chiral Ni electrode allows for observing the OER at a more favourable potential: about 50 mV (i.e. a cathodic, less positive, shift of the potential at which the oxygen evolution is observed).

Endoscopic medical images can suffer from uneven illumination, low contrast, and lack of texture information due to the use of point directional light sources and the presence of narrow tissue structures, posing diagnostic difficulties for physicians. In this paper, a deep learning-based su-pervised illumination enhancement network is designed for low-light endoscopic images, aiming to improve both global illumination and local details. Initially, a global illumination enhancement module is formulated utilizing a higher-order curve function to improve global illumination. Sec-ondly, a local feature extraction module incorporating dual attention is designed to capture local detailed features. Considering the significance of color fidelity in biomedical scenarios, the designed loss function prioritizes introducing color loss to alleviate image color distortion. Compared with seven state-of-the-art enhancement algorithms on Endo4IE endoscopic datasets, experimental re-sults show that the proposed method can better enhance low-light endoscopic images and avoid image color distortion. It provides an efficient method to enhance images captured by endoscopes which can effectively assist clinical diagnosis and treatment.

Nowadays, semantic segmentation is increasingly used in exploration by underwater robots, for example in autonomous navigation, so that the robot can recognise the nature and elements of its environment during the mission and act according to this classification to avoid collisions. Other applications can be found in the search for archaeological artefacts, in the inspection of underwater structures or in species monitoring. Therefore, it is necessary to try to improve the performance in these tasks as much as possible. To this end, we compare some methods for improving image quality and for data augmentation and test whether higher performance metrics can be achieved with both strategies. The experiments are performed with the SegNet implementations and the SUIM dataset with 8 common underwater classes to compare the obtained results with the already known ones. The results obtained with both strategies show that they are beneficial and lead to better performance results by achieving a mean IoU of 56% and an increased overall accuracy of 81.8%. The single result shows that there are 5 classes with an IoU value above 60% and only one class with an IoU value below 30%, which is a more reliable result and easier to use in real contexts.

Circular economy has recently emerged as a key strategy for promoting sustainability and reducing waste in various industrial sectors. This paper provides an overview of circularity in aerospace, wind energy, transportation, automotive and sports goods using data and information from the literature and the EC funded project "RECREATE". The survey reviews the different definitions, assessment methods and metrics used to explore and evaluate circularity, including assessment frameworks such as Life Cycle Assessment (LCA) and assessment indicators. Furthermore, explores the challenges, possibilities and the available tools for enhancing circularity, such as digital tools. The survey highlights the importance of a holistic and systemic technique to circularity, concerning all stakeholders along the value chain. Overall, this study aims to contribute to a better understanding of circular economy and provides insights for future research.

The drastically increasing amount of plastic waste is causing an environmental crisis that requires innovative technologies for recycling post-consumer plastics to achieve waste valorization while meeting environmental quality goals. Biocatalytic depolymerization mediated by enzymes has emerged as an efficient and sustainable alternative for plastic treatment and recycling. A variety of plastic- degrading enzymes have been discovered from microbial sources. Meanwhile, protein engineering has been exploited to modify and optimize plastic-degrading enzymes. This review highlights the recent trends and up-to-date advances in mining novel plastic-degrading enzymes through state-of-the-art omics-based techniques and improving the enzyme catalytic efficiency and stability via various protein engineering strategies. Future research prospects and challenges are also discussed

This paper develops a detail image signal enhancement that makes images perceived as clearer and more resolved and so is more effective for higher resolution displays. We observe that the local variant signal enhancement makes images more vivid, and the more revealed granular signals harmonically embedded on the local variant signals make images more resolved. Based on this observation, we develop a method that not only emphasizes the local variant signals by scaling up the frequency energy in accordance with human visual perception, but also strengths up the granular signals by embedding the alpha-rooting enhanced frequency components. The proposed energy scaling method emphasizes the detail signals in texture images and rarely boosts noisy signals in plain images. In addition, to avoid the local ringing artifact, the proposed method adjusts the enhancement direction to be parallel to the underlying image signal direction. It was verified through the subjective and objective quality evaluations that the developed method makes images perceived as clearer and highly resolved.

Zika virus (ZIKV) is a flavivirus that originated in Africa but emerged in Latin America in 2015. In this region, other flaviviruses such as Dengue (DENV), West Nile, and Yellow Fever Virus (YFV) also circulate, allowing for possible antigenic cross-reactivity to impact viral infections and immune responses. Studies have found antibody mediated enhancement between DENV and ZIKV, but the impact of YFV antibodies on ZIKV infection has not been fully explored. ZIKV infections cause congenital syndromes, such as microcephaly, necessitating further research into ZIKV vertical transmission through the placental barrier. Recent advancements in biomedical engineering have generated co-culture methods that allow for in vitro recapitulation of the maternal: fetal interface. This study utilized a transwell assay, which is a co-culture model utilizing human placental syncytiotrophoblasts, fetal umbilical cells, and a differentiating embryoid body to replicate the maternal: fetal axis. To determine if cross reactive YFV vaccine antibodies impact the pathogenesis of ZIKV across the maternal fetal axis, maternal syncytiotrophoblasts were inoculated with ZIKV or ZIKV incubated with YFV vaccine anti-sera, and viral load was measured 72 hours post inoculation. The data show that the impact of YFV on ZIKV replication is cell line dependent. In differentiating embryoids, the presence of YFV antibodies enhanced ZIKV infection. Since viral pathogenesis, and the impact of antigenic cross-reactive antibodies, is cell line specific at the maternal-fetal axis, this suggests there may be discreet mechanisms that impact congenital ZIKV infections.

Ellagic acid, a polyphenolic compound present in fruits and berries, has recently been object of extensive research for its antioxidant activity, which might be useful for the prevention and treatment of cancer, cardiovascular pathologies, and neurodegenerative disorders. Its protective role justifies numerous attempts to include it in functional food preparations and in dietary supplements not only to limit the unpleasant collateral effects of chemotherapy. However, ellagic acid use as chemopreventive agent has been debated because of its poor bioavailability associated to low solubility, limited permeability, first pass effect, and interindividual variability in gut microbial transformations. To overcome these drawbacks, various strategies for oral administration including solid dispersions, micro-nanoparticles, inclusion complexes, self-emulsifying systems, polymorphs have been proposed. Here, we have listed an updated description of pursued micro/nanotechnological approaches focusing on the fabrication processes and the features of the obtained products, as well as on the positive results yielded by in vitro and in vivo studies in comparison to the raw material. The micro/nano-sized formulations here described might be exploited for pharmaceutical delivery of this active, as well as for the production of nutritional supplements or for the enrichment of novel foods.

In this manuscript we report new effects of resonance detuning on various dynamical parameters of a generic 3-wave system. Namely, for suitably chosen values of detuning the variation range of amplitudes can be significantly wider than for exact resonance. Moreover, the range of energy variation is not symmetric with respect to the sign of the detuning. Finally, the period of the energy oscillation exhibits non-monotonic dependency on the magnitude of detuning. These results have important theoretical implications where nonlinear resonance analysis is involved, such as geophysics, plasma physics, fluid dynamics. Numerous practical applications are envisageable e.g. in energy harvesting systems.

Coalbed Methane(CBM) production enhancement for single wells is a big problem to CBM industrialization. Low production is due to insufficient gas generation by thermogenic. Luckily, Biogenic gas was found in many areas and its supply is assumed to improve coalbed methane production. Therefore, microbial simulation experiment will demonstrate the effectiveness of the assumption. From microbial simulation experiment on different coal ranks, it is found that microbes can use coals to produce biogas under laboratory conditions. With different temperatures for different experiments, it turns out that the gas production at 35 ℃ is greater than that at 15℃,indicating that 35℃ is more suitable for microbes to produce gas. According to quantitative experiments, adding exogenous nutrients or exogenous bacteria can improve CBM production. Moreover, the production enhancement ratio can reach up to 115% under the condition of adding exogenous bacterial species, while the ratio for adding nutrients can be up to 144%.

In biology molecules and macromolecules like sugars, proteins, DNA, and RNA are of utter importance. Detecting their presence as well as their conformation is still a challenge in many cases. It is well known that the vibrational states of such molecules lie from the infrared to the TeraHertz range. Spectroscopy can be used to detect such compounds and probe their conformation. Still, terahertz spectroscopy on biosample is a challenge for two main reasons: water absorption; and the small size of the samples. The sample volume is smaller than the cube of the TeraHertz wavelength; the light matter interactions are thus extremely reduced. In this paper, we present the design, fabrication, characterization and the first typical uses of a biophotonic device aiming at increasing light matter interaction to enable terahertz spectroscopy of minute samples on a broad band (0.2–2 THz). We demonstrate time domain spectroscopy experiments on few µl samples showing the validity of our approach.

In the seasonally frozen regions, during the grouting of prestressed bridge ducts in low-temperature environments, incompletely cured grout materials undergo volumetric changes due to the freeze-thaw cycling, resulting in structural cracks along the prestressing ducts of the bridge, thereby diminishing the bridge's operational lifespan. To investigate the frost heaving characteristics of grout materials under freeze-thaw cycles and propose potential enhancements, this study was devised to conduct frost heaving stress tests on grout materials. Through this research, we gained insights into how various additives affect the frost heaving stress characteristics of grout materials under freeze-thaw cycles. Incorporating analyses of free water content, setting time, compressive strength, as well as macroscopic examinations such as XRD and SEM, this study delves into the mechanisms for enhancing frost heaving characteristics of grout materials. Furthermore, it proposes a research approach that utilizes multiple admixtures to improve the frost heaving properties of grout materials. Through frost heaving stress tests and other macroscopic experiments, the study investigates the influence of these combined admixtures on frost heaving stress in grout materials and elucidates the underlying improvement mechanisms. The results indicate that reducing the water-cement ratio, incorporating calcium formate, sulfoaluminate cement, air-entraining agents, and carbamide all have a positive impact on mitigating frost heaving stress in grout materials. However, the improvement mechanisms differ, and employing a single measure alone is insufficient to effectively reduce frost heaving stress while meeting performance criteria such as compressive strength, setting time, and flowability. Free water content emerges as a crucial indicator determining the magnitude of frost heaving stress in grout materials, with 11.5% of free water content representing the critical threshold for frost heaving in grout materials. Utilizing composite admixtures can simultaneously decrease free water content, lower the freezing point of free water, and alleviate frost heaving deformation, resulting in more efficient reduction of frost heaving stress. When the admixture content reaches 9.9%, frost heaving stress is eliminated, and the comprehensive performance parameters including compressive strength, setting time, and flowability meet the specified requirements.

Pretilachlor is a chloroacetamide herbicide, mainly used for the control of weeds and broadleaf weeds in rice, and widely used in China. For the detection of residues of pretilachlor in the en-vironment and food, a highly sensitive and specific monoclonal antibody against pretilachlor was prepared, and the half maximum inhibitory concentration (IC50) of the monoclonal antibody was validated to be 31.47±2.35 μg/L. An indirect competitive ELISA (ic-ELISA) based on the antibody with a linear range of 6.25~100 μg/L was developed for the detection of pretilachlor residues in the environment and food crops. The specificity of the antibody was explained by computer simula-tions and experimental validation. No cross-reactivity of this monoclonal antibody to alachlor, acetochlor and metalaxyl, and it cross-reacted less than 3.0% to both butachlor and propisochlor. The limits of detection (LOD) for pretilachlor in lake, rice, and soil samples were 4.83~5.23 μg/L. The recoveries of all samples were 78.3%~91.3%. The ic-ELISA method was validated by high-performance liquid chromatography, thus, it can be used for residue detection of pretilachlor in the environment and grains.

Immune checkpoint blockade therapy has shown successful clinical outcomes in multiple human cancers. In dogs, several types of tumors resemble human tumors in many respects. Therefore, several groups have developed the anti-dog programmed cell death ligand 1 (dPD-L1) monoclonal antibodies (mAbs) and showed efficacy in several canine tumors. To examine the abundance of dPD-L1 in canine tumors, anti-dPD-L1 diagnostic mAbs for immunohistochemistry are required. In this study, we immunized the peptide in the dPD-L1 intracellular domain, and established anti-dPD-L1 mAbs, L1Mab-352 (mouse IgG1, kappa) and L1Mab-354 (mouse IgG1, kappa). In enzyme-linked immunosorbent assay, L1Mab-352 and L1Mab-354 showed high binding affinity to the dPD-L1 peptide, and the dissociation constants (KD) were determined as 6.9 ×10-10 M and 7.2 ×10-10 M, respectively. Furthermore, L1Mab-352 and L1Mab-354 were applicable for the detection of dPD-L1 in immunohistochemical analysis in paraffin-embedded dPD-L1-expressed cells. These results indicated that L1Mab-352 and L1Mab-354 are useful for detecting dPD-L1 in immunohistochemical analysis.

Breast cancer patients with high levels of HER2 (human epidermal growth factor receptor 2) expression had worse clinical outcomes. Anti-HER2 monoclonal antibody (mAb) is the most important therapeutic modality for HER2-positive breast cancer. We previously immunized mice with the ectodomain of HER2 to create the anti-HER2 mAb, H2Mab-77 (mouse IgG1, kappa). This was then altered to produce H2Mab-77-mG2a-f, an afucosylated mouse IgG2a. In the present work, we examined the reactivity of H2Mab-77-mG2a-f and antitumor effects against breast cancers in vitro and in vivo. BT-474, an endogenously HER2-expressed breast cancer cell line, was identified by H2Mab-77-mG2a-f with a strong binding affinity [a dissociation constant (KD): 5.0 × 10-9 M]. H2Mab-77-mG2a-f could stain HER2 of breast cancer tissues in immunohistochemistry and detect HER2 protein in western blot analysis. Furthermore, H2Mab-77-mG2a-f demonstrated strong antibody-dependent cellular cytotoxicity (ADCC) and complement-dependent cytotoxicity (CDC) for BT-474 cells. MDA-MB-468, a HER2-negative breast cancer cell line, was unaffected by H2Mab-77-mG2a-f. Additionally, in the BT-474-bearing tumor xenograft model, H2Mab-77-mG2a-f substantially suppressed tumor development when compared to the control mouse IgG2a mAb. In contrast, the HER2-negative MDA-MB-468-bearing tumor xenograft model showed no response to H2Mab-77-mG2a-f. These findings point to the possibility of H2Mab-77-mG2a-f as a treatment regimen by showing that it has antitumor effects on HER2-positive breast tumors.

Data on immunogenicity, immune response persistency, and safety of COVID-19 boosters in patients with comorbidities are limited. Therefore, we aimed to evaluate and compare three different boosters in individuals who received two doses of the BBIBP-CorV vaccine including underlying diseases and healthy cases as control. One hundred forty subjects including 63 ones with at least one of three underlying diseases (UD) (including obesity, hypertension, and diabetes mellitus) and 77 healthy ones (HC) who had received a booster dose (either PastoCovac Plus or PastoCovac or BBIBP-CorV) were enrolled. The presence of SARS-CoV-2 antibodies was assessed before the booster injection and 28, 60, 90, and 180 days after it. Moreover, the adverse events (AEs) were recorded on days 7 and 21 post-booster shot for evaluating safety outcomes. Significantly increased titers of anti-spike, anti-RBD, and neutralizing antibodies were observed in both UD and HC groups 28 days after the booster dose, although the titer rise of anti-spike IgG and anti-RBD IgG was insignificantly inferior in the UD group compared to the HC group. All antibodies’ titers declined, with no significant differences between the two groups over time. Notably, all specific antibodies persisted up to 180 days; particularly the neutralizing antibody in both groups. Furthermore, no significant difference in antibody levels was observed between each UD subgroup and the HC group, except for neutralizing antibodies in the hypertension sub-group. PastoCovac Plus and PastoCovac boosters induced higher antibodies’ fold rise in UD individuals than BBIBP-CorV booster recipients. Safety outcomes did not show any serious AEs after the booster injection. The overall incidence of AEs post the booster injection was higher in the UD group than the HC group. Furthermore, the highest systemic AEs rate was reported in the UD group receiving the BBIBP-CorV booster. In conclusion, administration of COVID-19 boosters can equally induce robust and persistent humoral immune responses in individuals with or without UD primarily vaccinated with 2-doses of the BBIBP-CorV. Protein-based boosters with higher antibodies' fold rise and lower AEs in individuals with comorbidities might be considered a better choice for these individuals.

Despite the recent approval of novel immunotherapies, as immunomodulatory drug, proteasome inhibitors and anti-CD38 monoclonal antibodies, Multiple Myeloma (MM) remains incurable and the acquisition of triple-refractoriness leads to really dismal outcomes, in even earlier lines of therapy. More recently, innovative therapeutic strategies targeting B cell maturation antigen (BCMA), highly expressed on the plasma cell surface, are drawing different future landscapes in terms of effectiveness and outcomes. Belantamab Mafodotin, a first-in-class anti-BCMA antibody drug conjugates, demonstrated good efficacy and safety profile in triple-refractory patients in the phase 2 DREAMM-2 trial and it was approved for the treatment of MM triple-exposed patients with >4 prior lines of therapy. Here, starting from Belantamab Mafodotin clinical trials also exploring combination studies and different schedules in order to improve its efficacy and toxicity, we focused on real life experiences all over the world, which have confirmed clinical trial data and encourage further Belantamab Mafodotin investigations

CC chemokine receptor 6 (CCR6) is one of the members of G protein-coupled receptor (GPCR) family that is upregulated in many immune-related cells, including B lymphocytes, effector and memory T cells, regulatory T cells, and immature dendritic cells. Coordination between CCR6 and its ligand CC motif chemokine ligand 20 (CCL20) is deeply involved in the pathogenesis of various diseases, such as cancer, autoimmune diseases, and psoriasis. Therefore, CCR6 is an attractive target for therapy and is being investigated as a diagnostic marker for patients. In a previous study, we developed an anti-mouse CCR6 (mCCR6) monoclonal antibody (mAb), C6Mab-13 (rat IgG1, kappa), applicable for flow cytometry by immunizing a rat with N-terminal peptide of mCCR6. This study investigated the binding epitope of C6Mab-13 using enzyme-linked immunosorbent assay (ELISA) and surface plasmon resonance (SPR) methods with the synthesized point mutated-peptides within 1-20 amino acids region of mCCR6. In ELISA, C6Mab-13 lost the reaction to the alanine-substituted peptide of D11A. The epitope of C6Mab-13 was identified to be Asp11 in ELISA. Furthermore, in SPR analysis, the dissociation constants (KD) could not be calculated for G9A and D11A mutants due to lack of binding. The SPR analysis demonstrated that the C6Mab-13 epitope comprises Gly9 and Asp11. Taken together, the key binding epitope of C6Mab-13 was determined to be around Asp11 on mCCR6. Based on the epitope information, C6Mab-13 could be useful for further functional analysis of mCCR6 in future studies.

Abstract: Enfortumab vedotin (EV), an antibody-drug conjugate directed against Nectin-4, signif-icantly prolonged survival when compared with standard chemotherapy in patients with locally advanced or metastatic urothelial carcinoma who previously received platinum-based chemo-therapy and a PD-1 or PD-L1 inhibitor. The confirmed overall response rate in the phase 3 EV301 trial leading to approval was 40.6%. However, no data have been published about the activity in brain metastases. Here, we present three patients from different centers with brain metastases receiving EV. A 58-year-old male Caucasian patient, who was heavily pretreated for urothelial carcinoma with visceral metastases and a solitary clinically active brain metastasis, started on EV 1.25 mg/kg on days 1, 8, and 15 of a 28-day cycle. The first evaluation after three cycles of EV showed a partial remission by RECIST v1.1 with a near complete response in the brain metastasis and disappear-ance of the neurological complaints. The patient is currently still receiving EV. A second, 74-year-old male patient started on the same regimen, after previous progression on platinum-based chemotherapy and maintenance avelumab. The patient achieved complete response and remained on therapy for five months. However, therapy was discontinued at the patient’s re-quest. Shortly after, he developed new leptomeningeal metastases. Upon rechallenge with EV, there was a significant reduction in the diffuse meningeal infiltration. A third, 50-year-old male Caucasian patient also received EV, after previous progression on cisplatin-gemcitabine and ate-zolizumab maintenance followed by palliative whole brain radiotherapy and two cycles of vin-flunine. The first evaluation after three cycles of EV showed a significant reduction of the brain metastases. The patient is currently still receiving EV. These are the first reports on efficacy of EV in patients with urothelial carcinoma and active brain metastases.

Zika virus (ZIKV) outbreaks in Central and South America caused severe public health problems in 2015 and 2016. These outbreaks were finally contained through several methods, including mosquito control using insecticides and repellents. Additionally, the development of herd immunity in these countries might have contributed to containing the epidemic. While ZIKV is mainly transmitted by mosquito bites, mucosal transmission via bodily fluids, including the semen of infected individuals, has also been reported. We evaluated the effect of mucosal ZIKV infection on continuous subcutaneous challenges in a cynomolgus monkey model. Repeated intravaginal inoculations of ZIKV did not induce detectable viremia or clinical symptoms, and all animals developed a potent neutralizing antibody, protecting animals from the subsequent subcutaneous superchallenge. These results suggest that viral replication at mucosal sites can induce protective immunity without causing systemic viremia or symptoms.

Regulatory T cells (Tregs) are major drivers behind immunosuppressive mechanisms and present a major hurdle for cancer therapy. Tregs are characterized by high expression of CD25, which is a potentially valuable target for Treg depletion to alleviate immune suppression. The preclinical anti-CD25 (αCD25) antibody, clone PC-61, has met with modest anti-tumor activity, due to its capacity to clear Tregs from circulation and lymph nodes but not those that reside in the tumor. Optimization of the Fc domain of this antibody clone has been shown to enhance intratumoral Treg depletion capacity. Here, we generated a stable cell line that produces optimized recombinant Treg depleting antibodies. A genome engineering strategy in which CRISPR-Cas9 was combined with homology directed repair (CRISPR-HDR) was utilized to optimize the Fc domain of the hybridoma PC-61 for effector functions by switching it from the original rat IgG1 to a mouse IgG2a isotype. In a syngeneic tumor mouse model the resulting αCD25-m2a antibody mediated effective depletion of tumor resident Tregs leading to a high effector T cell (Teff) to Treg ratio. Moreover, combination of the αCD25-m2a with αPD-L1 treatment augmented tumor eradication in mice, demonstrating the potential for αCD25 as a cancer immunotherapy.