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Outside-in engineering of cadherin endocytosis using a conformation strengthening antibody
Abstract P-cadherin, a crucial cell-cell adhesion protein which is overexpressed in numerous malignant cancers, is a popular target for drug delivery antibodies. However, molecular guidelines for engineering antibodies that can be internalized upon binding to P-cadherin are unknown. Here, we use a combination of biophysical, biochemical, and cell biological methods to demonstrate that trapping the P-cadherin extracellular region in an X-dimer adhesive conformation triggers cadherin endocytosis via an outside-in signaling mechanism. We show that the anti-cancer drug delivery monoclonal antibody CQY684, traps P-cadherin in an X-dimer conformation and strengthens this adhesive structure. Formation of stable X-dimers results in the phosphorylation of p120-catenin, a suppressor of cadherin endocytosis. This triggers the dissociation of p120-catenin from the X-dimer cytoplasmic region, which increases P-cadherin turnover and targets the cadherin-antibody complex to the lysosome. Our results establish an outside-in signaling mechanism that provides fundamental insights into how cells regulate adhesion and that can be exploited by anti-cadherin antibodies for intracellular drug delivery.
Inotodiol induces hepatocellular carcinoma apoptosis by activation of MAPK/ERK pathway
Hepatocellular carcinoma(HCC) has a high mortality and morbidity rate and seriously jeopardizes human life. Chemicals and chemotherapeutic agents have been experiencing problems such as side effects and drug resistance in the treatment of HCC, which cannot meet the needs of clinical treatment. Therefore, finding novel low-toxicity and high-efficiency anti-hepatocellular carcinoma drugs and exploring their mechanisms of action have become the current problems to be solved in the treatment of HCC. Several studies have reported anticancer effects of inotodiol. This study focuses on the anticancer effect of inotodiol in HCC cells and its molecular mechanism, aiming to explore its anticancer effect in depth. The CCK8 assay was utilized to assess cell viability, the scratch assay was utilized to detect migration ability, the clone formation assay was utilized to detect clonogenic ability, and flow cytometry was utilized to analyze apoptosis and cell cycle. Animal experiments was utilized to verify the inhibitory effect of inotodiol on HCC. Meanwhile, western blotting was utilized to detect proteins associated with apoptosis, cell cycle and MAPK/ERK pathway. These results showed that inotodiol has the ability to promote apoptosis, as well as inhibit the ability of cell proliferation, migration, and clonogenic ability. The cell cycle was arrested in G1 phase, when the expression of CDK2, CDK4, CDK6 and Cyclin D were inhibited. In addition, inotodiol showed to induce apoptosis, characterized by an increase in Bax expression, a decrease in Bcl-2, Bcl-XL and MCL1 expression, the initiation of cleaved PARP1 and cleaved caspase 3, and inhibition of the MAPK/ERK pathway. Animal studies demonstrated that inotodiol possessed the ability to suppress tumor growth in nude mice models, at the same time, there was no significant impact on the body weight and organs of the mice. In conclusion, the findings presented herein compellingly suggest that inotodiol may serve as a promising candidate for the treatment of hepatocellular carcinoma (HCC).
Meta-analysis of RNA-Seq datasets allows a better understanding of P. tricornutum cellular biology, a requirement to improve the production of Biologics
Abstract The marine diatom Phaeodactylum tricornutum is currently used for various industrial applications, including the pharmaceutical industry as a cost-effective cell biofactory to produce Biologics. Recent studies demonstrated that P. tricornutum can produce functional monoclonal antibodies, such application is currently limited by the production yield that hinders industrialization. Therefore, it is necessary to understand and control the cell biology of P. tricornutum to improve the Biologics production yield. Transcriptomic analyses have recently been used by the pharmaceutical industry to improve the production of Biologics in mammalian cells, especially Biologics titer and cell productivity. Hence, in the present work, we performed a meta-analysis of seven publicly available RNA-Seq datasets from different strains of P. tricornutum, for which the culture conditions were chosen as similar as possible. We analyzed the differential expression of genes that are involved in biological processes that are well known to potentially impact the bioproduction and critical quality attributes of Biologics. Therefore, the expression of genes involved in the N-glycan biosynthesis, protein export and secretion, protein quality control and proteasome, as well as those encoding proteases were analyzed and compared. The results pave the way towards optimizing Biologics production in P. tricornutum and highlight that the Pt4, Pt3 Ov and Pt8 strains seem to be the most promising P. tricornutum strains.
Discovery of ketene/acetyl as a potential receptor for hydrogen-transfer reactions in zeolites
Revolutionizing colorectal cancer detection: A breakthrough in microbiome data analysis
The emergence of Next Generation Sequencing (NGS) technology has catalyzed a paradigm shift in clinical diagnostics and personalized medicine, enabling unprecedented access to high-throughput microbiome data. However, the inherent high dimensionality, noise, and variability of microbiome data present substantial obstacles to conventional statistical methods and machine learning techniques. Even the promising deep learning (DL) methods are not immune to these challenges. This paper introduces a novel feature engineering method that circumvents these limitations by amalgamating two feature sets derived from input data to generate a new dataset, which is then subjected to feature selection. This innovative approach markedly enhances the Area Under the Curve (AUC) performance of the Deep Neural Network (DNN) algorithm in colorectal cancer (CRC) detection using gut microbiome data, elevating it from 0.800 to 0.923. The proposed method constitutes a significant advancement in the field, providing a robust solution to the intricacies of microbiome data analysis and amplifying the potential of DL methods in disease detection.
scRNA seq of an F1 cross of Marek’s disease resistant and susceptible chickens identifies allele specific expression signatures enriched in transcription modulators
Abstract Marek’s disease (MD), a T cell lymphoma disease in chickens, is caused by the Marek’s disease virus (MDV) found ubiquitously in the poultry industry. Genetically resistant Line 63 (L6) and susceptible Line 72 (L7) chickens have been instrumental to research on avian immune system response to MDV infection. In this study we characterized molecular signatures unique to splenic immune cell types across different genetic backgrounds 6 days after infection. Using three populations, L6, L7, and an F1 cross between L6xL7, we evaluated the immune cell transcriptome of responding cell types using single cell RNA sequencing. Several MDV genes were found expressed mainly in cytotoxic T cells while ICP4 and MEQ MDV genes were expressed across infected cell types. Using the F1 we quantified allele specific expression (ASE) of biallelic SNPs and found biased expression of parental alleles specific to immune cell subtypes. We identified 22 SNPs with ASE in response to MDV infection mapped to gene rich regions surrounding 59 genes of critical importance for chromatin remodeling and transcriptional regulation. Histone deacetylase genes (HDAC1 and HDAC8) had increased expression of L6 alleles, while small nuclear RNA genes (SNORA68 and SNORA72) expressed higher levels of L7 alleles with infection in T cell subsets. SNPs with ASE also mapped genes important for an adequate immune response including GNLY (cytotoxic activity) and PDIA3 (component of MHC class I peptide loading complex), and genes known to promote viral replication (MCM5 and EIF3M). These results show that functional variants associated with susceptibility to MD may have a bigger impact in subsets of immune cell types, and by characterizing the transcriptomes of these subtypes we can unravel molecular signatures specific to MD genomic resistance.
VSTM2L protects prostate cancer cells against ferroptosis via inhibiting VDAC1 oligomerization and maintaining mitochondria homeostasis
Trajectory of the arterial-alveolar oxygen gradient in COPD for a decade
Background Chronic respiratory failure (CRF) is a critical complication in patients with chronic obstructive pulmonary disease (COPD) and is characterized by an increase in the arterial-alveolar oxygen gradient (A-aDO2). The long-term trajectory and prognostic significance remain unclear. This study aimed to assess the prognostic impact of A-aDO2 and elucidate its trajectory over ten years. Methods We enrolled 170 outpatients with COPD from a prospective cohort study. Arterial blood gas (ABG) analyses were conducted annually for ten years while monitoring the development of CRF. Results 157 patients completed the observation period, of whom 21 developed CRF (CRF group) and 136 did not (non-CRF group). In the CRF group, there was a gradual increase in A-aDO2 along with decreases in partial pressure of oxygen (PaO2) and partial pressure of carbon dioxide (PaCO2) over ten years, although there were no changes in the non-CRF group. The CRF group had higher baseline A-aDO2 and higher ΔA-aDO2 in the first year than the non-CRF group (3.76 vs. 0.42 Torr/year, p = 0.030). Kaplan-Meier analyses, and multivariate Cox proportional hazards analysis revealed that both baseline A-aDO2 and ΔA-aDO2 were significantly associated with the development of CRF. Retrospective tracking from the initiation of long-term oxygen therapy (LTOT) revealed significant increases in A-aDO2 from 5 years prior to LTOT initiation in the CRF group when compared to the non-CRF group. Conclusions An increasing trend in A-aDO2 may be a significant sign for the future development of CRF. A transition of the annual change of A-aDO2 from a stable state to a deterioration phase can serve as a prognostic factor for developing CRF within 5 years.
Metal-organic frameworks-derived CaO/ZnO composites as stable catalysts for biodiesel production from soybean oil at room temperature
Transition from the topological to the chaotic in the nonlinear Su–Schrieffer–Heeger model
Abstract Recent studies on topological materials are expanding into the nonlinear regime, while the central principle, namely the bulk–edge correspondence, is yet to be elucidated in the strongly nonlinear regime. Here, we reveal that nonlinear topological edge modes can exhibit the transition to spatial chaos by increasing nonlinearity, which can be a universal mechanism of the breakdown of the bulk–edge correspondence. Specifically, we unveil the underlying dynamical system describing the spatial distribution of zero modes and show the emergence of chaos. We also propose the correspondence between the absolute value of the topological invariant and the dimension of the stable manifold under sufficiently weak nonlinearity. Our results provide a general guiding principle to investigate the nonlinear bulk–edge correspondence that can potentially be extended to arbitrary dimensions.
Hypercapnic warm-up and re-warm-up–A novel experimental approach in swimming sprint
The purpose of this study was to determine the effective warm-up protocol using an added respiratory dead space (ARDS) 1200 ml volume mask to determine hypercapnic conditions, on the swimming velocity of the 50 m time trial front crawl. Eight male members of the university swimming team, aged 19–25, performed three different warm-up protocols: 1) standardized warm-up in water (WUCON); 2) hypercapnic warm-up in water (WUARDS); 3) hypercapnic a 20-minute transition phase on land, between warm-up in water and swimming test (RE-WUARDS). The three warm-up protocols were implemented in random order every 7th day. After each protocol, the 50 m time trial front crawl swimming (swimming test) was performed. The fastest time trial swimming of 50 m front crawl was achieved after the hypercapnic transition phase (RE-WUARDS) protocol and was 27.5 ± 1.6 seconds, 1.2% faster than hypercapnic warm-up protocol (p = 0.01). This result was confirmed by a higher swimming average speed of the exercise test after RE-WUARDS compared to WUARDS (p = 0.01). The use of ARDS provoked a state of tolerable hypercapnia (obtaining carbon dioxide concentration in arterialized blood pCO2 > 45 mmHg) achieving a post-warm-up of WUARDS value 49.7 ± 5.9 mmHg (compared to the control condition which was a statistically significant difference p = 0.02) and before time trial RE-WUARDS 45.7 ± 2.1 mmHg (p = 0.01 compared to WUCON). After breathing through the 1200 ml ARDS mask during the 20-minute re-warm-up phase, there was a trend of faster time trial among participants compared to the control condition, and statistically significantly faster times compared to WUARDS, indicating that further study is appropriate to verify the efficacy of the proposed method to improve swimming efficiency.
Postoperative complications and long-term outcomes after total and subtotal thyroidectomy: a retrospective study
Publisher Correction: Biomass carbon emissions from nickel mining have significant implications for climate action
HIV-1 resistance mutations and genetic diversity among children failing antiretroviral treatment in five healthcare facilities in Benin, West Africa
Background Antiretroviral treatment increases the risk of accumulation of resistance mutations that negatively impact the possibilities of future treatment. This study aimed to present the frequency of HIV-1 antiretroviral resistance mutations and the genetic diversity among children with virological failure in five pediatric care facilities in Benin. Methods A cross-sectional study was carried out from November 20, 2020, to November 30, 2022, in children under 15 years of age who failed ongoing antiretroviral treatment at five facilities care in Benin (VL > 3log10 on two consecutive realizations three months apart). Viral loads were measured using the m2000 RealTime Abbott platform. Genotyping was carried out with the commercial Viroseq kit. Sequences were read on the ABI 3500 sequencer and then edited with ViroSeqHIVv3.0 software. The HIV drug resistance database at Stanford University was used to identify mutations and viral subtypes were assigned by phylogenetic analyses. Results The HIV-1 pol gene was sequenced in 47 participants with virological failure of antiretroviral treatment. The median age was 120 [Interquartile Range 90–144] months. The prevalent treatment was EFV base regimen (22/47; 46.8%). Median viral load was 4.39 log10 [IQR 3.81–4.86 log10] respectively. Resistance testing was successful among (37/47; 78.72%) children, resistance mutations were detected in (32/37; 86.48%) children, and (29/32; 90.62%) had at least one surveillance drug resistance mutation. Respectively (25/32; 78.12%), (28/32; 87.5%), (4/32; 12.90%), (22/32; 68.75%) had at least one resistance mutation associated with NRTIs, NNRTIs, PIs and NNRTIs+NRTIs. (12/32; 37.5%) of children carried mutations related to TAMs. the most frequently NRTIs identified were M184V (21/62; 33.9%) followed by TAMs (20/62; 32.2%) and T69G/D (2/62; 3.2%)s. Among mutations associated with NNRTIs K103N represented (18/64; 28.1%) followed by P225H (7/64; 10.9%). The I54V (3/6; 50%) mutation is the major PI observed. Genetic diversity is characterized by a preponderance of CRF02_AG (72%, 23/32), followed by unique recombinant forms (URFs) (25%, 8/32) and one subtype G. Conclusion A high rate of mutations has been observed in children. These data underline the importance of implementing routine genotypic testing in the biological monitoring of infected children to anticipate the accumulation of resistance mutations and thus compromise the treatment options available in Benin.
Effect of metformin on the level of aqueous humor inflammatory cytokines in patients with cataract
Intricacies of human–AI interaction in dynamic decision-making for precision oncology
Abstract AI decision support systems can assist clinicians in planning adaptive treatment strategies that can dynamically react to individuals’ cancer progression for effective personalized care. However, AI’s imperfections can lead to suboptimal therapeutics if clinicians over or under rely on AI. To investigate such collaborative decision-making process, we conducted a Human–AI interaction study on response-adaptive radiotherapy for non-small cell lung cancer and hepatocellular carcinoma. We investigated two levels of collaborative behavior: model-agnostic and model-specific; and found that Human–AI interaction is multifactorial and depends on the complex interrelationship between prior knowledge and preferences, patient’s state, disease site, treatment modality, model transparency, and AI’s learned behavior and biases. In summary, some clinicians may disregard AI recommendations due to skepticism; others will critically analyze AI recommendations on a case-by-case basis; clinicians will adjust their decisions if they find AI recommendations beneficial to patients; and clinician will disregard AI recommendations if deemed harmful or suboptimal and seek alternatives.
The genetic architecture of resistance to flubendiamide insecticide in Helicoverpa armigera (Hübner)
Insecticide resistance is a major problem in food production, environmental sustainability, and human health. The cotton bollworm Helicoverpa armigera is a globally distributed crop pest affecting over 300 crop species. H. armigera has rapidly evolved insecticide resistance, making it one of the most damaging pests worldwide. Understanding the genetic basis of insecticide resistance provides insights to develop tools, such as molecular markers, that can be used to slow or prevent the evolution of resistance. We explore the genetic architecture of H. armigera resistance to a widely used insecticide, flubendiamide, using two complementary approaches: genome-wide association studies (GWAS) in wild-caught samples and quantitative trait locus (QTL) mapping in a controlled cross of susceptible and resistant laboratory strains. Both approaches identified one locus on chromosome 2, revealing two SNPs within 976 bp that can be used to monitor field resistance to flubendiamide. This was the only region identified using linkage mapping, though GWAS revealed additional sites associated with resistance. Other loci identified by GWAS in field populations contained known insecticide detoxification genes from the ATP-binding cassette family, ABCA1, ABCA3, ABCF2 and MDR1. Our findings revealed an oligogenic genetic architecture, contrasting previous reports of monogenic resistance associated with the ryanodine receptor. This work elucidates the genetic basis of rapidly evolving insecticide resistance and will contribute to developing effective insecticide resistance management strategies.