Preclinical Evaluation of STI-8811, a Novel Antibody Drug Conjugate Targeting BCMA for the Treatment of Multiple Myeloma.

Treatment for patients with Multiple Myeloma (MM) has experienced rapid development and improvement in recent years, however, patients continue to experience relapse and MM remains largely incurable. B cell maturation antigen (BCMA) has been widely recognized as a promising target for treatment of MM due to its exclusive expression in B cell linage cells and its critical role in the growth and survival of malignant plasma cells. Here, we introduce STI-8811, a BCMA-targeting antibody drug conjugate linked to an auristatin-derived duostatin payload via an enzymatically cleavable peptide linker, using our proprietary C-lock technology. STI-8811 exhibits target specific binding activity and rapid internalization, leading to G2/M cell cycle arrest, caspase 3/7 activation and apoptosis in BCMA-expressing tumor cells in vitro. Soluble BCMA (sBCMA) is shed by MM cells into the blood and increases with disease progression, competing for ADC binding and reducing its efficacy. We report enhanced cytotoxic activity in the presence of high levels of sBCMA compared to a belantamab mafodotin biosimilar (J6M0-mcMMAF). STI-8811 demonstrated greater in vivo activity than J6M0-mcMMAF in solid and disseminated multiple myeloma models, including tumor models with low BCMA expression and/or in large solid tumors representing soft tissue plasmacytomas. In Cynomolgus monkeys, STI-8811 was well tolerated, with toxicities consistent with other BCMA targeting ADCs with auristatin payloads in clinical studies. STI-8811 has the potential to outperform current clinical candidates with lower toxicity and higher activity under conditions found in patients with advanced disease.

A Supramolecular Fluorescent Sensor Array Composed of Conjugated Fluorophores and Cucurbit[7]uril for Bacterial Recognition.

Bacterial infections have emerged as a significant contributor to global mortality and morbidity rates. Herein, we introduce a dual fluorescence "turn-on" supramolecular sensor array composed of three assembled complexes (C1-C3), formed from three positively charged fluorophores (A1-A3) and one cucurbit[7]uril (CB[7]). The ability of this three-element array to simultaneously recognize 10 bacterial species within just 30 s was remarkable, boasting an impressive 100% accuracy. Additionally, the array excelled at distinguishing among various bacterial mixtures and enabled the quantitative detection of common bacterial strains. Notably, it has been skillfully applied to differentiate 10 bacterial samples in urine, achieving excellent differentiation and showcasing promising potential for medical diagnostic applications.

Arsenic-induced downregulation of BRWD3 suppresses proliferation and induces apoptosis in lung adenocarcinoma cells through the p53 and p65 pathways.

Bromodomain and WD-repeat domain-containing protein 3 (BRWD3) exhibits high expression in lung adenocarcinoma (LUAD) tissues and cells; however, its function in arsenic-induced toxicological responses remains unclear. This study aimed to investigate BRWD3 expression in response to arsenic-induced conditions and its impact on the proliferation and apoptosis of LUAD cell line SPC-A1 upon BRWD3 knockdown. The results revealed a decrease in BRWD3 expression in SPC-A1 cells treated with sodium arsenite (NaAsO2), but not sodium arsenite's metabolites. BRWD3 knockdown suppressed cell proliferation and induced apoptosis in SPC-A1 cells. Western blot analysis revealed that BRWD3 knockdown resulted in the upregulation of p53, phospho-p53-Ser392, and its downstream factors including MDM2, Bak, and Bax. Additionally, we observed the downregulation of p65, phospho-p65-Ser276, phospho-p65-Ser536, and its downstream factors, including IκBα, BIRC3, XIAP and CIAP1. Moreover, polymerase chain reaction analysis showed that BRWD3 knockdown also resulted in the downregulation of proliferation-related genes and upregulation of apoptosis-related genes. In conclusion, BRWD3 mediated proliferation and apoptosis via the p53 and p65 pathways in response to arsenic exposure, suggesting potential implications for LUAD treatment through BRWD3 downregulation by arsenic.

Bayesian Optimization of Low-Temperature Nonthermal Plasma Jet Sintering of Nanoinks.

In response to the escalating demand for flexible devices in applications such as wearables, sensors, and touch panels, there is a need for innovative fabrication approaches for devices made from nanomaterial-based inks. Subsequent to ink deposition, a pivotal stage in device manufacturing typically involves high-temperature sintering, posing challenges for heat-sensitive substrates. Nonthermal plasma jet sintering utilizing an atmospheric pressure dielectric barrier discharge (DBD) plasma jet enables sintering at room temperature and standard pressure, facilitating the sintering of printed nanoparticle films without compromising substrate or film surface integrity. However, determining optimal plasma jet sintering conditions can be challenging due to multiple processing variables with intricate interrelationships. This work employed Bayesian optimization (BO) and machine learning (ML) to identify optimal values for seven primary plasma jet sintering variables. Optimization yielded a 99.2% increase in the measured electrical conductivity for plasma jet-sintered indium tin oxide (ITO) films after five rounds of experiments. Moreover, the optimal sintering conditions achieved an electrical conductivity that was 81.4% of conventional furnace sintering at 300 °C, but was three times faster and with a peak substrate temperature below 47 °C. This result demonstrates the prospect of applying BO to optimize processing techniques for emerging low-temperature requirements.

Alterations of pathogen transmission patterns and attenuated immune stimulation might be the cause of increased adult respiratory infections cases in 2023, results from a multi-center study in mainland China.

Background: Several respiratory infections outbreaks have been observed in mainland China after reduction of non-pharmaceutical interventions. Other countries have seen increases in respiratory infections outside typical seasons post-COVID-19, warranting investigation into underlying causes. Methods: We established monitoring networks for suspected respiratory infection in 14 tertiary hospitals nationwide. PCR for SARS-CoV-2, influenza A and B were performed on 3708 respiratory specimens and deep sequencing were conducted to identify co-infections or newly emerging microbes in 2023. Viral evolutionary analysis was completed. We retrospectively detected serum antibody level for various respiratory pathogens from 4324 adults without respiratory infections over 7 years to observe its dynamic curves. Findings: SARS-CoV-2 and influenza A were the main pathogens during outbreaks in 2023, bacterial-virus and bacterial-bacterial co-infections were most detected, but community co-infections didn't significantly increase pneumonia incidence. Different SARS-CoV-2 and influenza variants were present in different outbreaks, and no novel pathogens were found. The epidemiological patterns of influenza A, COVID-19 and etc. were altered, exhibiting characteristics of being "staggered" compared to most global regions, and potentially led to "overlapping prevalence". Binding antibody testing showed regular fluctuation, without significant decrease against common respiratory pathogens in adults. Influenza A antibody stimulation was attenuated during the 2023 outbreak. Conclusions: "Misaligned" alteration in seasonal respiratory disease patterns possibly caused combined epidemics, leading to cases spike in China, 2023. In adults, antibody levels didn't show significant decline, but reduced immune response to influenza during 2020-2023 emphasizes the need for consistent vaccination during pandemics.

Longitudinal Analysis of Humoral and Cellular Immune Response up to 6 Months after SARS-CoV-2 BA.5/BF.7/XBB Breakthrough Infection and BA.5/BF.7-XBB Reinfection.

The rapid mutation of SARS-CoV-2 has led to multiple rounds of large-scale breakthrough infection and reinfection worldwide. However, the dynamic changes of humoral and cellular immunity responses to several subvariants after infection remain unclear. In our study, a 6-month longitudinal immune response evaluation was conducted on 118 sera and 50 PBMC samples from 49 healthy individuals who experienced BA.5/BF.7/XBB breakthrough infection or BA.5/BF.7-XBB reinfection. By studying antibody response, memory B cell, and IFN-γ secreting CD4+/CD8+ T cell response to several SARS-CoV-2 variants, we observed that each component of immune response exhibited distinct kinetics. Either BA.5/BF.7/XBB breakthrough infection or BA.5/BF.7-XBB reinfection induces relatively high level of binding and neutralizing antibody titers against Omicron subvariants at an early time point, which rapidly decreases over time. Most of the individuals at 6 months post-breakthrough infection completely lost their neutralizing activities against BQ.1.1, CH.1.1, BA.2.86, JN.1 and XBB subvariants. Individuals with BA.5/BF.7-XBB reinfection exhibit immune imprinting shifting and recall pre-existing BA.5/BF.7 neutralization antibodies. In the BA.5 breakthrough infection group, the frequency of BA.5 and XBB.1.16-RBD specific memory B cells, resting memory B cells, and intermediate memory B cells gradually increased over time. On the other hand, the frequency of IFN-γ secreting CD4+/CD8+ T cells induced by WT/BA.5/XBB.1.16 spike trimer remains stable over time. Overall, our research indicates that individuals with breakthrough infection have rapidly declining antibody levels but have a relatively stable cellular immunity that can provide some degree of protection from future exposure to new antigens.

Insights into tolerance mechanisms of earthworms (Eisenia fetida) in copper-contaminated soils by integrating multi-omics analyses.

Earthworms can resist high levels of soil copper (Cu) contamination and play an essential role in absorbing them effectively. However, the molecular mechanisms underlying Cu tolerance in earthworms are poorly understood. To address this research gap, we studied alterations of Eisenia fetida in antioxidant enzymes, gut microbiota, metabolites, and genes under varying levels of Cu exposure soils (0, 67.58, 168.96, 337.92 mg/kg). Our results revealed a reduction in antioxidant enzyme activities across all treatment groups, indicating an adaptive response to alleviate Cu-induced oxidative stress. Analysis of gut microbiota revealed a significant increase in the abundance of bacteria associated with nutrient uptake and Cu2+ excretion under Cu stress. Furthermore, metabolomic analysis discovered an increase in certain metabolites associated with energy metabolism, such as pyruvic acid, L-malic acid, and fumaric acid, as Cu concentration escalated. These results suggested that enhanced energy supply contributes to the elevated tolerance of E. fetida towards Cu. Additionally, transcriptome analysis not only identified crucial detoxification genes (Hsp70, CTSL, GST, CHAC, and GCLC), but also confirmed the critical role of glutathione metabolism as a key pathway in E. fetida Cu detoxification processes. These findings provide a new perspective on the molecular mechanisms of Cu tolerance in earthworms.

Prognostic value of poly-microorganisms detected by droplet digital PCR and pathogen load kinetics in sepsis patients: a multi-center prospective cohort study.

This study aimed to investigate the prognostic value of a novel droplet digital polymerase chain reaction (DDPCR) assay in sepsis patients. In this prospective cohort study, univariable and multivariable Cox regressions were used to assess risk factors for 28-day mortality. We also monitored pathogen load together with clinical indicators in a subgroup of the cohort. A total of 107 sepsis patients with positive baseline DDPCR results were included. Detection of poly-microorganisms [adjusted hazard ratio (HR) = 3.19; 95% confidence interval (CI) = 1.34-7.62; P = 0.009], high Charlson Comorbidity Index (CCI) score (adjusted HR = 1.14; 95% CI = 1.01-1.29; P = 0.041), and Sequential Organ Failure Assessment (SOFA) score (adjusted HR = 1.18; 95% CI = 1.05-1.32; P = 0.005) at baseline were independent risk factors for 28-day mortality while initial pathogen load was not associated (adjusted HR = 1.17; 95% CI = 0.82-1.66; P = 0.385). Among 63 patients with serial DDPCR results, an increase in pathogen load at days 6-8 compared to baseline was a risk factor for 28-day mortality (P = 0.008). Also, pathogen load kinetics were significantly different between day-28 survivors and nonsurvivors (P = 0.022), with a decline overtime only in survivors and an increase from days 3 and 4 to days 6-8 in nonsurvivors. Using DDPCR technique, we found that poly-microorganisms detected and increased pathogen load a week after sepsis diagnosis were associated with poor prognosis.IMPORTANCEThis prospective study was initiated to explore the prognostic implications of a novel multiplex PCR assay in sepsis. Notably, our study was the largest cohort of sepsis with droplet digital polymerase chain reaction pathogen monitoring to date, allowing for a comprehensive evaluation of the prognostic significance of both pathogen species and load. We found that detection of poly-microorganisms was an independent risk factors for 28-day mortality. Also, pathogen load increase 1 week after sepsis diagnosis was a risk factor for 28-day mortality, and differential pathogen load kinetics were identified between day-28 survivors and nonsurvivors. Overall, this study demonstrated that pathogen species and load were highly correlated with sepsis prognosis. Patients exhibiting conditions mentioned above face a more adverse prognosis, suggesting the potential need for an escalation of antimicrobial therapy.Registered at ClinicalTrials.gov (NCT05190861).

The role of sialidase Neu1 in respiratory diseases.

Neu1 is a sialidase enzyme that plays a crucial role in the regulation of glycosylation in a variety of cellular processes, including cellular signaling and inflammation. In recent years, numerous evidence has suggested that human NEU1 is also involved in the pathogenesis of various respiratory diseases, including lung infection, chronic obstructive pulmonary disease (COPD), asthma, and pulmonary fibrosis. This review paper aims to provide an overview of the current research on human NEU1 and respiratory diseases.

A Dual Fluorescence Turn-On Sensor Array Formed by Poly(para-aryleneethynylene) and Aggregation-Induced Emission Fluorophores for Sensitive Multiplexed Bacterial Recognition.

Bacterial infections have emerged as the leading causes of mortality and morbidity worldwide. Herein, we developed a dual-channel fluorescence "turn-on" sensor array, comprising six electrostatic complexes formed from one negatively charged poly(para-aryleneethynylene) (PPE) and six positively charged aggregation-induced emission (AIE) fluorophores. The 6-element array enabled the simultaneous identification of 20 bacteria (OD600=0.005) within 30s (99.0 % accuracy), demonstrating significant advantages over the array constituted by the 7 separate elements that constitute the complexes. Meanwhile, the array realized different mixing ratios and quantitative detection of prevalent bacteria associated with urinary tract infection (UTI). It also excelled in distinguishing six simulated bacteria samples in artificial urine. Remarkably, the limit of detection for E. coli and E. faecalis was notably low, at 0.000295 and 0.000329 (OD600), respectively. Finally, optimized by diverse machine learning algorithms, the designed array achieved 96.7 % accuracy in differentiating UTI clinical samples from healthy individuals using a random forest model, demonstrating the great potential for medical diagnostic applications.

2023: A year of accomplishments for the 13 Science Citation Index Expanded- and Emerging Sources Citation Index-indexed Baishideng journals.

In 2023, Baishideng Publishing Group (Baishideng) routinely published 47 open-access journals, including 46 English-language journals and 1 Chinese-language journal. Our successes were accomplished through the collective dedicated efforts of Baishideng staffs, Editorial Board Members, and Peer Reviewers. Among these 47 Baishideng journals, 7 are included in the Science Citation Index Expanded (SCIE) and 6 in the Emerging Sources Citation Index (ESCI). With the support of Baishideng authors, company staffs, Editorial Board Members, and Peer Reviewers, the publication work of 2023 is about to be successfully completed. This editorial summarizes the 2023 activities and accomplishments of the 13 SCIE- and ESCI-indexed Baishideng journals, outlines the Baishideng publishing policy changes and additions made this year, and highlights the unique advantages of Baishideng journals.

Hybrid Printing of Fully Integrated Microfluidic Devices for Biosensing.

The advent of 3D printing has facilitated the rapid fabrication of microfluidic devices that are accessible and cost-effective. However, it remains a challenge to fabricate sophisticated microfluidic devices with integrated structural and functional components due to limited material options of existing printing methods and their stringent requirement on feedstock material properties. Here, a multi-materials multi-scale hybrid printing method that enables seamless integration of a broad range of structural and functional materials into complex devices is reported. A fully printed and assembly-free microfluidic biosensor with embedded fluidic channels and functionalized electrodes at sub-100 µm spatial resolution for the amperometric sensing of lactate in sweat is demonstrated. The sensors present a sensitive response with a limit of detection of 442 nm and a linear dynamic range of 1-10 mm, which are performance characteristics relevant to physiological levels of lactate in sweat. The versatile hybrid printing method offers a new pathway toward facile fabrication of next-generation integrated devices for broad applications in point-of-care health monitoring and sensing.

Enhanced neutralization of SARS-CoV-2 variant BA.2.86 and XBB sub-lineages by a tetravalent COVID-19 vaccine booster.

Emerging SARS-CoV-2 sub-lineages like XBB.1.5, XBB.1.16, EG.5, HK.3 (FLip), and XBB.2.3 and the variant BA.2.86 have recently been identified. Understanding the efficacy of current vaccines on these emerging variants is critical. We evaluate the serum neutralization activities of participants who received COVID-19 inactivated vaccine (CoronaVac), those who received the recently approved tetravalent protein vaccine (SCTV01E), or those who had contracted a breakthrough infection with BA.5/BF.7/XBB virus. Neutralization profiles against a broad panel of 30 sub-lineages reveal that BQ.1.1, CH.1.1, and all the XBB sub-lineages exhibit heightened resistance to neutralization compared to previous variants. However, despite their extra mutations, BA.2.86 and the emerging XBB sub-lineages do not demonstrate significantly increased resistance to neutralization over XBB.1.5. Encouragingly, the SCTV01E booster consistently induces higher neutralizing titers against all these variants than breakthrough infection does. Cellular immunity assays also show that the SCTV01E booster elicits a higher frequency of virus-specific memory B cells. Our findings support the development of multivalent vaccines to combat future variants.

Risk of reinfection and severity with the predominant BA.5 Omicron subvariant China, from December 2022 to January 2023.

Data on reinfection in large Asian populations are limited. In this study, we aimed to evaluate the reinfection rate, disease severity, and time interval between the infections in the symptomatic and asymptomatic populations which are firstl infected with BA.2 Omicron Variant. We retrospectively included adult patients with COVID-19 discharged from four designated hospitals between 27 April 2021 and 30 November 2022, who were interviewed via telephone from 29 January to 1 March 2023. Univariable and multivariable analyses were used to explore risk factors associated with reinfection. A total of 16,558 patients were followed up, during the telephone survey of an average of 310.0 days, 1610 (9.72%) participants self-reported reinfection. The mean time range of reinfection was 257.9 days. The risks for reinfection were analysed using multivariable logistic regression. Patients with severe first infection were at higher risk for reinfection (aORs, 2.50; P < 0.001). The male (aORs,0.82; P < 0.001), the elderly (aORs, 0.44; P < 0.001), and patients with full vaccination (aORs, 0.67; P < 0.001) or booster (aORs, 0.63; P < 0.001) had the lower risk of reinfection. Patients over 60 years of age (aORs,9.02; P = 0.006) and those with ≥2 comorbidities (aORs,11.51; P = 0.016). were at higher risk for severe reinfection. The number of clinical manifestations of reinfection increases in people with severe first infection (aORs, 2.82; P = 0.023). The overall reinfection rate was 9.72%, and the reinfection rate of Omicron-to-Omicron subvariants was 9.50% at one year. The severity of Omicron-Omicron reinfection decreased. Data from our clinical study may provide clinical evidence and bolster response preparedness for future COVID-19 reinfection waves.

Multilocus Distance-Regulated Sensor Array for Recognition of Polyphenols via Machine Learning and Indicator Displacement Assay.

Developing new strategies to construct sensor arrays that can effectively distinguish multiple natural components with similar structures in mixtures is an exceptionally challenging task. Here, we propose a new multilocus distance-modulated indicator displacement assay (IDA) strategy for constructing a sensor array, incorporating machine learning optimization to identify polyphenols. An 8-element array, comprising two fluorophores and their six dynamic covalent complexes (C1-C6) formed by pairing two fluorophores with three distinct distance-regulated quenchers, has been constructed. Polyphenols with diverse spatial arrangements and combinatorial forms compete with the fluorophores by forming pseudocycles with quenchers within the complexes, leading to varying degrees of fluorescence recovery. The array accurately and effectively distinguished four tea polyphenols and 16 tea varieties, thereby demonstrating the broad applicability of the multilocus distance-modulated IDA array in detecting polyhydroxy foods and natural medicines.

Discovery of novel cMET-targeting antibody Fab drug conjugates as potential treatment for solid tumors with highly expressed cMET.

BACKGROUND: Solid tumors are becoming prevalent affecting both old and young populations. Numerous solid tumors are associated with high cMET expression. The complexity of solid tumors combined with the highly interconnected nature of the cMET/HGF pathway with other cellular pathways make the pursuit of finding an effective treatment extremely challenging. The current standard of care for these malignancies is mostly small molecule-based chemotherapy. Antibody-based therapeutics as well as antibody drug conjugates are promising emerging classes against cMET-overexpressing solid tumors. RESEARCH DESIGN AND METHODS: In this study, we described the design, synthesis, in vitro and in vivo characterization of cMET-targeting Fab drug conjugates (FDCs) as an alternative therapeutic strategy. The format is comprised of a Fab conjugated to a potent cytotoxic drug via a cleavable linker employing lysine-based and cysteine-based conjugation chemistries. RESULTS: We found that the FDCs have potent anti-tumor efficacies in cancer cells with elevated overexpression of cMET. Moreover, they demonstrated a remarkable anti-tumor effect in a human gastric xenograft mouse model. CONCLUSIONS: The FDC format has the potential to overcome some of the challenges presented by the other classes of therapeutics. This study highlights the promise of antibody fragment-based drug conjugate formats for the treatment of solid tumors.

Hybrid Data-Driven Discovery of High-Performance Silver Selenide-Based Thermoelectric Composites.

Optimizing material compositions often enhances thermoelectric performances. However, the large selection of possible base elements and dopants results in a vast composition design space that is too large to systematically search using solely domain knowledge. To address this challenge, a hybrid data-driven strategy that integrates Bayesian optimization (BO) and Gaussian process regression (GPR) is proposed to optimize the composition of five elements (Ag, Se, S, Cu, and Te) in AgSe-based thermoelectric materials. Data is collected from the literature to provide prior knowledge for the initial GPR model, which is updated by actively collected experimental data during the iteration between BO and experiments. Within seven iterations, the optimized AgSe-based materials prepared using a simple high-throughput ink mixing and blade coating method deliver a high power factor of 2100 µW m-1 K-2 , which is a 75% improvement from the baseline composite (nominal composition of Ag2 Se1 ). The success of this study provides opportunities to generalize the demonstrated active machine learning technique to accelerate the development and optimization of a wide range of material systems with reduced experimental trials.