Affinity gaps among B cells in germinal centers drive the selection of MPER precursors.

Current prophylactic human immunodeficiency virus 1 (HIV-1) vaccine research aims to elicit broadly neutralizing antibodies (bnAbs). Membrane-proximal external region (MPER)-targeting bnAbs, such as 10E8, provide exceptionally broad neutralization, but some are autoreactive. Here, we generated humanized B cell antigen receptor knock-in mouse models to test whether a series of germline-targeting immunogens could drive MPER-specific precursors toward bnAbs. We found that recruitment of 10E8 precursors to germinal centers (GCs) required a minimum affinity for germline-targeting immunogens, but the GC residency of MPER precursors was brief due to displacement by higher-affinity endogenous B cell competitors. Higher-affinity germline-targeting immunogens extended the GC residency of MPER precursors, but robust long-term GC residency and maturation were only observed for MPER-HuGL18, an MPER precursor clonotype able to close the affinity gap with endogenous B cell competitors in the GC. Thus, germline-targeting immunogens could induce MPER-targeting antibodies, and B cell residency in the GC may be regulated by a precursor-competitor affinity gap.

Vaccination induces broadly neutralizing antibody precursors to HIV gp41.

A key barrier to the development of vaccines that induce broadly neutralizing antibodies (bnAbs) against human immunodeficiency virus (HIV) and other viruses of high antigenic diversity is the design of priming immunogens that induce rare bnAb-precursor B cells. The high neutralization breadth of the HIV bnAb 10E8 makes elicitation of 10E8-class bnAbs desirable; however, the recessed epitope within gp41 makes envelope trimers poor priming immunogens and requires that 10E8-class bnAbs possess a long heavy chain complementarity determining region 3 (HCDR3) with a specific binding motif. We developed germline-targeting epitope scaffolds with affinity for 10E8-class precursors and engineered nanoparticles for multivalent display. Scaffolds exhibited epitope structural mimicry and bound bnAb-precursor human naive B cells in ex vivo screens, protein nanoparticles induced bnAb-precursor responses in stringent mouse models and rhesus macaques, and mRNA-encoded nanoparticles triggered similar responses in mice. Thus, germline-targeting epitope scaffold nanoparticles can elicit rare bnAb-precursor B cells with predefined binding specificities and HCDR3 features.

Light-driven nanoscale vectorial currents.

Controlled charge flows are fundamental to many areas of science and technology, serving as carriers of energy and information, as probes of material properties and dynamics1 and as a means of revealing2,3 or even inducing4,5 broken symmetries. Emerging methods for light-based current control5-16 offer particularly promising routes beyond the speed and adaptability limitations of conventional voltage-driven systems. However, optical generation and manipulation of currents at nanometre spatial scales remains a basic challenge and a crucial step towards scalable optoelectronic systems for microelectronics and information science. Here we introduce vectorial optoelectronic metasurfaces in which ultrafast light pulses induce local directional charge flows around symmetry-broken plasmonic nanostructures, with tunable responses and arbitrary patterning down to subdiffractive nanometre scales. Local symmetries and vectorial currents are revealed by polarization-dependent and wavelength-sensitive electrical readout and terahertz (THz) emission, whereas spatially tailored global currents are demonstrated in the direct generation of elusive broadband THz vector beams17. We show that, in graphene, a detailed interplay between electrodynamic, thermodynamic and hydrodynamic degrees of freedom gives rise to rapidly evolving nanoscale driving forces and charge flows under the extremely spatially and temporally localized excitation. These results set the stage for versatile patterning and optical control over nanoscale currents in materials diagnostics, THz spectroscopies, nanomagnetism and ultrafast information processing.

Ultrapotent influenza hemagglutinin fusion inhibitors developed through SuFEx-enabled high-throughput medicinal chemistry.

Seasonal and pandemic-associated influenza strains cause highly contagious viral respiratory infections that can lead to severe illness and excess mortality. Here, we report on the optimization of our small-molecule inhibitor F0045(S) targeting the influenza hemagglutinin (HA) stem with our Sulfur-Fluoride Exchange (SuFEx) click chemistry-based high-throughput medicinal chemistry (HTMC) strategy. A combination of SuFEx- and amide-based lead molecule diversification and structure-guided design led to identification and validation of ultrapotent influenza fusion inhibitors with subnanomolar EC50 cellular antiviral activity against several influenza A group 1 strains. X-ray structures of six of these compounds with HA indicate that the appended moieties occupy additional pockets on the HA surface and increase the binding interaction, where the accumulation of several polar interactions also contributes to the improved affinity. The compounds here represent the most potent HA small-molecule inhibitors to date. Our divergent HTMC platform is therefore a powerful, rapid, and cost-effective approach to develop bioactive chemical probes and drug-like candidates against viral targets.

Detecting shifts in nonlinear dynamics using Empirical Dynamic Modeling with Nested-Library Analysis.

Abrupt changes in system states and dynamical behaviors are often observed in natural systems; such phenomena, named regime shifts, are explained as transitions between alternative steady states (more generally, attractors). Various methods have been proposed to detect regime shifts from time series data, but a generic detection method with theoretical linkage to underlying dynamics is lacking. Here, we provide a novel method named Nested-Library Analysis (NLA) to retrospectively detect regime shifts using empirical dynamic modeling (EDM) rooted in theory of attractor reconstruction. Specifically, NLA determines the time of regime shift as the cutting point at which sequential reduction of the library set (i.e., the time series data used to reconstruct the attractor for forecasting) optimizes the forecast skill of EDM. We illustrate this method on a chaotic model of which changing parameters present a critical transition. Our analysis shows that NLA detects the change point in the model system and outperforms existing approaches based on statistical characteristics. In addition, NLA empirically detected a real-world regime shift event revealing an abrupt change of Pacific Decadal Oscillation index around the mid-1970s. Importantly, our method can be easily generalized to various systems because NLA is equation-free and requires only a single time series.

Room-Temperature Anisotropic Actuation Driven by a Synergistic Order-Disorder and Displacive Phase Transition in a Ferroelectric Crystal.

Actuating materials convert different forms of energy into mechanical responses. To satisfy various application scenarios, they are desired to have rich categories, novel functionalities, clear structure-property relationships, fast responses, and, in particular, giant and reversible shape changes. Herein, we report a phase transition-driven ferroelectric crystal, (rac-3-HOPD)PbI3 (3-HOPD = 3-hydroxypiperidine cation), showing intriguingly large and anisotropic room-temperature actuating behaviors. The crystal consists of rigid one-dimensional [PbI3] anionic chains running along the a-axis and discrete disk-like cations loosely wrapping around the chains, leaving room for anisotropic shape changes in both the b- and c-axes. The shape change is switched by a ferroelectric phase transition occurring at around room temperature (294 K), driven by the exceptionally synergistic order-disorder and displacive phase transition. The rotation of the cations exerts internal pressure on the stacking structure to trigger an exceptionally large displacement of the inorganic chains, corresponding to a crystal lattice transformation with length changes of +24.6% and -17.5% along the b- and c-axis, respectively. Single crystal-based prototype devices of circuit switches and elevators have been fabricated by exploiting the unconventional negative temperature-dependent actuating behaviors. This work provides a new model for the development of multifunctional mechanically responsive materials.

Rational Design of 2D Metal Halide Perovskites with Low Congruent Melting Temperature and Large Melt-Processable Window.

Metal halide perovskites (MHPs) have garnered significant attention due to their distinctive optical and electronic properties, coupled with excellent processability. However, the thermal characteristics of these materials are often overlooked, which can be harnessed to cater to diverse application scenarios. We showcase the efficacy of lowering the congruent melting temperature (Tm) of layered 2D MHPs by employing a strategy that involves the modification of flexible alkylammonium through N-methylation and I-substitution. Structural-property analysis reveals that the N-methylation and I-substitution play pivotal roles in reducing hydrogen bond interactions between the organic components and inorganic parts, lowering the rotational symmetry number of the cation and restricting the residual motion of the cations. Additional I···I interactions enhance intermolecular interactions and lead to improved molten stability, as evidenced by a higher viscosity. The 2D MHPs discussed in this study exhibit low Tm and wide melt-processable windows, e.g., (DMIPA)2PbI4 showcasing a low Tm of 98 °C and large melt-processable window of 145 °C. The efficacy of the strategy was further validated when applied to bromine-substituted 2D MHPs. Lowering the Tm and enhancing the molten stability of the MHPs hold great promise for various applications, including glass formation, preparation of high-quality films for photodetection, and fabrication of flexible devices.

The angiogenic role of the alpha 9-nicotinic acetylcholine receptor in triple-negative breast cancers.

Nicotine acts as an angiogenic factor by stimulating endogenous cholinergic pathways. Several subtypes of nicotinic acetylcholine receptors (nAChRs) have been demonstrated to be closely correlated to the formation and progression of different types of cancers. Recently, several studies have found that nicotinic acetylcholine receptors α9 (α9-nAChRs) are highly expressed in breast tumors, especially in tumors derived from patients diagnosed at advanced stages. In vitro studies have demonstrated that activation of α9-nAChRs is associated with increased proliferation and migration of breast cancer. To study the tumor-promoting role of α9-nAChRs in breast cancers, we generated a novel anti-α9-nAChR and methoxy-polyethylene glycol (mPEG) bispecific antibody (α9 BsAb) for dissecting the molecular mechanism on α9-nAChR-mediated tumor progression. Unexpectedly, we discovered the angiogenic role of α9-nAChR in nicotine-induced neovascularization of tumors. It revealed α9 BsAbs reduced nicotine-induced endothelial cell tube formation, blood vessel development in Matrigel plug assay and angiogenesis in microtube array membrane murine model (MTAMs). To unbraid the molecular mechanism of α9-nAChR in nicotine-mediated angiogenesis, the α9 BsAbs were applied and revealed the inhibitory roles in nicotine-induced production of hypoxia-inducible factor-2 alpha (HIF-2α), vascular endothelial growth factor A (VEGF-A), phosphorylated vascular endothelial growth factor receptor 2 (p-VEGFR2), vascular endothelial growth factor receptor 2 (VEGFR2) and matrix metalloproteinase-9 (MMP9) from triple-negative breast cancer cells (MDA-MB-231), suggesting α9-nAChRs played an important role in nicotine-induced angiogenesis. To confirm our results, the shRNA targeting α9-nAChRs was designed and used to silence α9-nAChR expression and then evaluated the angiogenic role of α9-nAChRs. The results showed α9 shRNA also played an inhibitory effect in blocking the nicotine-induced angiogenic signaling. Taken together, α9-nAChR played a critical role in nicotine-induced angiogenesis and this bispecific antibody (α9 BsAb) may serve as a potential therapeutic candidate for treatments of the α9 positive cancers.

Tumor-intrinsic IFNα and CXCL10 are critical for immunotherapeutic efficacy by recruiting and activating T lymphocytes in tumor microenvironment.

Tumor immunotherapies targeting PD-(L)1 exhibit anti-tumor efficacy in only 10-30% of patients with various cancers. Literature has demonstrated that a "hot tumor" which contains high T lymphocytes in the tumor microenvironment exhibits a better response to immunotherapies than a "cold tumor." This study aimed to investigate whether tumor-intrinsic IFNα and CXCL10 determine the recruitment and activation of CD8+ T cells to become "hot tumor." In this study, we found that CXCL10 overexpressed in a variety of tumors including lung, colon, and liver tumors with a correlation with PD-L1. High PD-L1 and CXCL10 are associated with better survival rates in tumor patients receiving immunotherapies. IFNs-downstream transcriptional factor IRF-1 and STAT1 were correlated with PD-L1 and CXCL10 expression. We demonstrated that IRF-1 and STAT1 were both bound with the promoters of PD-L1 and CXCL10, sharing the same signaling pathway and determining IFNs-mediated PD-L1 and CXCL10 expression. In addition, IFNα significantly increased activation marker IFNγ in PBMCs, promoting M1 type monocyte differentiation, CD4+ T, and CD8+ T cell activation. Particularly, we found that CD8+ T lymphocytes abundantly expressed CXCR3, a receptor of CXCL10, by flow cytometry, indicating that tumor-intrinsic CXCL10 potentially recruited CD8+ T in tumor microenvironment. To demonstrate the hypothesis, immunotherapy-sensitive CT26 and immunotherapy-resistant LL/2 were used and we found that CT26 cells exhibited higher IFNα, IFNγ, CXCL10, and PD-L1 levels compared to LL/2, leading to higher IFNγ expression in mouse splenocytes. Moreover, we found that CD8+ T cells were recruited by CXCL10 in vitro, whereas SCH546738, an inhibitor of CXCR3, inhibited T cell migration and splenocytes-mediated anti-tumor effect. We then confirmed that CT26-derived tumor was sensitive to αPD-L1 immunotherapy and LL/2-tumor was resistant, whereas αPD-L1 significantly increased T lymphocyte activation marker CD107a in CT26-derived BALB/c mice. In conclusion, this study revealed that CXCL10 expression is correlated with PD-L1 in tumors, sharing the same signaling pathway and associating with better immunotherapeutic efficacy. Further evidence in the syngeneic tumor models demonstrated that immunotherapy-sensitive CT26 intrinsically exhibited higher IFNα and CXCL10 compared to immunotherapy-resistant LL/2 to recruit and activate CD8+ T cells in the tumor microenvironment, exhibiting "hot tumor" characteristic of sensitizing αPD-L1 immunotherapies.

LPG 18:0 is a general biomarker of asthma and inhibits the differentiation and function of regulatory T cells.

BACKGROUND: The diagnosis, severity assessment, and development of therapeutic strategies for asthma are crucial aspects of disease management. Since biomarkers are reliable tools in disease management, we aimed to identify and explore asthma-associated biomarkers and investigate their mechanisms. METHODS: Lipidomics was used to profile serum glycerophospholipids in asthmatic patients and controls. The absolute concentration of lysophosphatidylglycerol (LPG) 18:0 was quantified in various asthma subtypes. Mouse asthma models were used to confirm its potential as a biomarker and investigate its mechanisms in vivo. The effects of LPG 18:0 on CD4+ T cell differentiation, proliferation, and apoptosis were assessed in vitro by flow cytometry, while mitochondrial dysfunction was evaluated through mitochondrial membrane potential, reactive oxygen species, and ATP production measurements. The intracellular mechanism of LPG 18:0 in Tregs was investigated using small molecule inhibitors. RESULTS: The serum glycerophospholipid profile varied between asthmatic patients and control group, with LPG 18:0 levels being notably higher in asthmatic patients, correlating with asthma severity and control level. In vivo and in vitro studies revealed that LPG18:0 impaired naïve CD4+ T cell differentiation into Tregs and compromised their suppressive function. Further investigation demonstrated that LPG18:0 treatment reduced the FOXP3 protein level via SIRT1-mediated deacetylation during Treg differentiation. CONCLUSIONS: This study identifies that serum levels of LPG 18:0 are generally elevated in asthmatics and serve as a biomarker for asthma. LPG 18:0 impairs Treg function via the NAD+/SIRT1/FOXP3 pathway. Our research reveals the potential of LPG18:0 as a biomarker for asthma, elucidating its role in asthma diagnosis and treatment.

Alkaline-Responsive, Self-Healable, and Conductive Copolymer Composites with Enhanced Mechanical Properties Tailored for Wearable Tech.

Despite significant advancements, current self-healing materials often suffer from a compromise between mechanical robustness and functional performance, particularly in terms of conductivity and responsiveness to environmental stimuli. Addressing this issue, the research introduces a self-healable and conductive copolymer, poly(ionic liquid-co-acrylic acid) (PIL-co-PAA), synthesized through free radical polymerization, and further optimized by incorporating thermoplastic polyurethane (TPU). This combination leverages the unique properties of each component, especially ion-dipole interactions and hydrogen bonds, resulting in a material that exhibits exceptional self-healing abilities and demonstrates enhanced mechanical properties and electrical conductivity. Moreover, the PIL-co-PAA/TPU films showcase alkaline-responsive behavior, a feature that broadens their applicability in dynamic environments. Through systematic characterization, including thermogravimetric analysis, tensile testing, and electrical properties measurements, the mechanisms behind the improved performance and functionality of these films are elucidated. The conductivities and ultimate tensile strength (σuts) of the PIL-co-PAA/TPU films regain 80% under 8 h healing process. To extend the applications for wearable devices, the self-healing properties of commercial cotton fabrics coated with the self-healable PIL-co-PAA are also investigated, demonstrating both self-healing and electrical properties. This study advances the understanding of self-healable conductive polymers and opens new avenues for their application in wearable technology.

Reversible Sensing Technologies Using Upcycled TPEE: Crafting pH and Light Responsive Materials towards Sustainable Monitoring.

Multiresponsive materials with reversible and durable characteristics are indispensable because of their promising applications in environmental change detections. To fabricate multiresponsive materials in mass production, however, complex reactions and impractical situations are often involved. Herein, a dual responsive (light and pH) spiropyran-based smart sensor fabricated by a simple layer-by-layer (LbL) assembly process from upcycled thermoplastic polyester elastomer (TPEE) materials derived from recycled polyethylene terephthalate (r-PET) is proposed. Positively charged chitosan solutions and negatively charged merocyanine-COOH (MC-COOH) solutions are employed in the LbL assembly technique, forming the chitosan-spiropyran deposited TPEE (TPEE-CH-SP) film. Upon UV irradiation, the spiropyran-COOH (SP-COOH) molecules on the TPEE-CH-SP film undergo the ring-opening isomerization, along with an apparent color change from colorless to purple, to transform into the MC-COOH molecules. By further exposing the TPEE-CH-MC film to hydrogen chloride (HCl) and nitric acid (HNO3) vapors, the MC-COOH molecules can be transformed into protonated merocyanine-COOH (MCH-COOH) with the simultaneous color change from purple to yellow.

Microbiome signatures associated with clinical stages of gastric Cancer: whole metagenome shotgun sequencing study.

BACKGROUND: Gastric cancer is one of the global health concerns. A series of studies on the stomach have confirmed the role of the microbiome in shaping gastrointestinal diseases. Delineation of microbiome signatures to distinguish chronic gastritis from gastric cancer will provide a non-invasive preventative and treatment strategy. In this study, we performed whole metagenome shotgun sequencing of fecal samples to enhance the detection of rare bacterial species and increase genome sequence coverage. Additionally, we employed multiple bioinformatics approaches to investigate the potential targets of the microbiome as an indicator of differentiating gastric cancer from chronic gastritis. RESULTS: A total of 65 patients were enrolled, comprising 33 individuals with chronic gastritis and 32 with gastric cancer. Within each group, the chronic gastritis group was sub-grouped into intestinal metaplasia (n = 15) and non-intestinal metaplasia (n = 18); the gastric cancer group, early stage (stages 1 and 2, n = 13) and late stage (stages 3 and 4, n = 19) cancer. No significant differences in alpha and beta diversities were detected among the patient groups. However, in a two-group univariate comparison, higher Fusobacteria abundance was identified in phylum; Fusobacteria presented higher abundance in gastric cancer (LDA scored 4.27, q = 0.041 in LEfSe). Age and sex-adjusted MaAsLin and Random Forest variable of importance (VIMP) analysis in species provided meaningful features; Bacteria_caccae was the most contributing species toward gastric cancer and late-stage cancer (beta:2.43, se:0.891, p:0.008, VIMP score:2.543). In contrast, Bifidobacterium_longum significantly contributed to chronic gastritis (beta:-1.8, se:0.699, p:0.009, VIMP score:1.988). Age, sex, and BMI-adjusted MasAsLin on metabolic pathway analysis showed that GLCMANNANAUT-PWY degradation was higher in gastric cancer and one of the contributing species was Fusobacterium_varium. CONCLUSION: Microbiomes belonging to the pathogenic phylum Fusobacteria and species Bacteroides_caccae and Streptococcus_anginosus can be significant targets for monitoring the progression of gastric cancer. Whereas Bifidobacterium_longum and Lachnospiraceae_bacterium_5_1_63FAA might be protection biomarkers against gastric cancer.

Feasibility of Using Needle Rinse Fluid for Cobas Human Papillomavirus (HPV) Assay in Diagnosing HPV+ Oropharyngeal Cancer with Neck Lymph Node Aspiration.

BACKGROUND: Human papillomavirus (HPV) is a crucial prognostic factor in oropharyngeal cancer (OPC). p16 is a surrogate marker for diagnosing HPV+ OPC, however it is not direct evidence of HPV existence. OBJECTIVE: The purpose of our study was to evaluate an HPV DNA test-Cobas HPV assay-in diagnosing HPV+ OPC through neck lymph node aspiration. METHODS: Patients with suspected neck mass who received fine needle aspiration (FNA) or core needle biopsy (CNB) at the National Taiwan University Hospital between January 2018 and December 2022 were reviewed. Besides routine cytology and pathology study, needle rinse fluid was collected for the Cobas HPV assay to detect high-risk HPV. RESULTS: We analyzed 137 patients with suspected lymph nodes, 32 (23.4%) of whom were HPV+ OPC patients and 105 (76.6%) of whom had non-HPV-related disease. FNA was performed in 31 patients and CNB was performed in 106 patients, according to the size and necrosis status of the lymph nodes. For diagnosing HPV+ OPC, CNB combined with p16 immunohistochemistry staining showed sensitivity of 93.3%, specificity of 97.8%, positive predictive value (PPV) of 87.5%, negative predictive value (NPV) of 98.9%, and accuracy of 97.2%. On the other hand, for the needle rinse Roche Cobas HPV assay, the test showed sensitivity of 96.9%, specificity of 100%, PPV of 100%, NPV of 99.1%, and accuracy of 99.3%. Compared with p16 IHC staining, the Cobas HPV test showed better PPV with statistical significance (p = 0.04). CONCLUSION: The Cobas HPV assay is a US FDA-approved, highly automated, and readily used technique to directly detect the presence of high-risk HPV. We recommend utilizing the Cobas HPV assay in combination with routine cytology or histopathology examination in the work-up of neck lymphadenopathy.

Artificial intelligence evaluation of coronary computed tomography angiography for coronary stenosis classification and diagnosis.

BACKGROUND: Ruling out obstructive coronary artery disease (CAD) using coronary computed tomography angiography (CCTA) is time-consuming and challenging. This study developed a deep learning (DL) model to assist in detecting obstructive CAD on CCTA to streamline workflows. METHODS: In total, 2929 DICOM files and 7945 labels were extracted from curved planar reformatted CCTA images. A modified Inception V3 model was adopted. To validate the artificial intelligence (AI) model, two cardiologists labelled and adjudicated the classification of coronary stenosis on CCTA. The model was trained to differentiate the coronary artery into binary stenosis classifications <50% and ≥50% stenosis. Using the quantitative coronary angiography (QCA) consensus results as a reference standard, the performance of the AI model and CCTA radiology readers was compared by calculating Cohen's kappa coefficients at patient and vessel levels. The net reclassification index was used to evaluate the net benefit of the DL model. RESULTS: The diagnostic accuracy of the AI model was 92.3% and 88.4% at the patient and vessel levels, respectively. Compared with CCTA radiology readers, the AI model had a better agreement for binary stenosis classification at both patient and vessel levels (Cohen kappa coefficient: .79 vs. .39 and .77 vs. .40, p < .0001). The AI model also exhibited significantly improved model discrimination and reclassification (Net reclassification index = .350; Z = 4.194; p < .001). CONCLUSIONS: The developed AI model identified obstructive CAD, and the model results correlated well with QCA results. Incorporating the model into the reporting system of CCTA may improve workflows.

Epoxide-Mediated Trans-Thioglycosylation and Application to the Synthesis of Oligosaccharides Related to the Capsular Polysaccharides of C. jejuni HS:4.

The enzyme-resistant thioglycosides are highly valuable immunogens because of their enhanced metabolic stability. We report the first synthesis of a family of thiooligosaccharides related to the capsular polysaccharides (CPS) of Campylobacter jejuni HS:4 for potential use in conjugate vaccines. The native CPS structures of the pathogen consist of a challenging repeating disaccharide formed with ß(1→4)-linked 6-deoxy-ß-D-ido-heptopyranoside and N-acetyl-D-glucosamine; the rare 6-deoxy-ido-heptopyranosyl backbone and ß-anomeric configuration of the former monosaccharide makes the synthesis of this family of antigens very challenging. So far, no synthesis of the thioanalogs of the CPS antigens have been reported. The unprecedented synthesis presented in this work is built on an elegant approach by using ß-glycosylthiolate as a glycosyl donor to open the 2,3-epoxide functionality of pre-designed 6-deoxy-ß-D-talo-heptopyranosides. Our results illustrated that this key trans-thioglycosylation can be designed in a modular and regio and stereo-selective manner. Built on the success of this novel approach, we succeeded the synthesis of a family of thiooligosaccharides including a thiohexasaccharide which is considered to be the desired antigen length and complexity for immunizations. We also report the first direct conversion of base-stable but acid-labile 2-trimethylsilylethyl glycosides to glycosyl-1-thioacetates in a one-pot manner.

The construction of machine learning-based predictive models for high-quality embryo formation in poor ovarian response patients with progestin-primed ovarian stimulation.

OBJECTIVE: To explore the optimal models for predicting the formation of high-quality embryos in Poor Ovarian Response (POR) Patients with Progestin-Primed Ovarian Stimulation (PPOS) using machine learning algorithms. METHODS: A retrospective analysis was conducted on the clinical data of 4,216 POR cycles who underwent in vitro fertilization (IVF) / intracytoplasmic sperm injection (ICSI) at Sichuan Jinxin Xinan Women and Children's Hospital from January 2015 to December 2021. Based on the presence of high-quality cleavage embryos 72 h post-fertilization, the samples were divided into the high-quality cleavage embryo group (N = 1950) and the non-high-quality cleavage embryo group (N = 2266). Additionally, based on whether high-quality blastocysts were observed following full blastocyst culture, the samples were categorized into the high-quality blastocyst group (N = 124) and the non-high-quality blastocyst group (N = 1800). The factors influencing the formation of high-quality embryos were analyzed using logistic regression. The predictive models based on machine learning methods were constructed and evaluated accordingly. RESULTS: Differential analysis revealed that there are statistically significant differences in 14 factors between high-quality and non-high-quality cleavage embryos. Logistic regression analysis identified 14 factors as influential in forming high-quality cleavage embryos. In models excluding three variables (retrieved oocytes, MII oocytes, and 2PN fertilized oocytes), the XGBoost model performed slightly better (AUC = 0.672, 95% CI = 0.636-0.708). Conversely, in models including these three variables, the Random Forest model exhibited the best performance (AUC = 0.788, 95% CI = 0.759-0.818). In the analysis of high-quality blastocysts, significant differences were found in 17 factors. Logistic regression analysis indicated that 13 factors influence the formation of high-quality blastocysts. Including these variables in the predictive model, the XGBoost model showed the highest performance (AUC = 0.813, 95% CI = 0.741-0.884). CONCLUSION: We developed a predictive model for the formation of high-quality embryos using machine learning methods for patients with POR undergoing treatment with the PPOS protocol. This model can help infertility patients better understand the likelihood of forming high-quality embryos following treatment and help clinicians better understand and predict treatment outcomes, thus facilitating more targeted and effective interventions.

α-Alkylation of ketones with primary alcohols by an active non-noble metal Cu/CuOx catalyst.

Development of convenient and effective heterogeneous non-noble metal catalysts for α-alkylation of ketones with alcohols is challenging in heterogeneous catalysis. Here, we report active non-noble metal Cu/CuOx catalysts for the construction of C-C bonds by the α-alkylation of ketones with alcohols through the borrowing hydrogen methodology. The optimal Cu/CuOx-250 catalyst exhibits good catalytic performance in the reactions to give the corresponding products in 50-96% yields. The Cu/CuOx catalysts are characterized by different analysis techniques such as XRD, TEM, XPS, H2-TPR, BET, and ICP. Moreover, the catalyst can be reused at least for five successive cycles without significant loss of activity. The present study provides meaningful insights into the development of non-noble metal heterogeneous catalysts for α-alkylation of ketones with alcohols.

Variations in the sleep-related breathing disorder index on polysomnography between men with HIV and controls: a matched case-control study.

BACKGROUND: Both sleep-related breathing disorders (SRBDs) and HIV infection can interfere with normal sleep architecture, and also cause physical and psychological distress. We aimed to understand the differences in the obstructive patterns, sleep architecture, physical and psychological distress when compared between people living with HIV (PLWH) and matched the severity of SRBDs controls. METHODS: A comparative study using matched case-control design was conducted. Men with HIV infection (case group) were enrolled from 2016 to 2019. A control group with HIV seronegative men were matched for SRBDs severity, and were selected from sleep medicine center database for comparison. RESULTS: The mean age of the 108 men (including 54 cases and 54 matched controls) was 33.75 years. Central-apnea index (CI) was higher in the case group rather than matched controls (mean CI, 0.34 vs. 0.17, p = 0.049). PLWH had a lower mean percentage of stage 3 sleep (10.26% vs. 13.94%, p = 0.034) and a higher percentage of rapid eye movement sleep (20.59% vs. 17.85%, p = 0.011) compared to matched controls. Nocturnal enuresis and sleepiness causing traffic accidents were more frequent complaint in PLWH compared to controls. CONCLUSIONS: Early detected SRBDs and subtypes in PLWH to begin treatment for the underlying cause could reduce the risk of sleepiness-related traffic accidents.