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The conversion of CO2 into liquid fuels, using only sunlight and water, offers a promising path to carbon neutrality. An outstanding challenge is to achieve high efficiency and product selectivity. Here, we introduce a wireless photocatalytic architecture for conversion of CO2 and water into methanol and oxygen. The catalytic material consists of semiconducting nanowires decorated with core-shell nanoparticles, with a copper-rhodium core and a chromium oxide shell. The Rh/CrOOH interface provides a unidirectional channel for proton reduction, enabling hydrogen spillover at the core-shell interface. The vectorial transfer of protons, electrons, and hydrogen atoms allows for switching the mechanism of CO2 reduction from a proton-coupled electron transfer pathway in aqueous solution to hydrogenation of CO2 with a solar-to-methanol efficiency of 0.22%. The reported findings demonstrate a highly efficient, stable, and scalable wireless system for synthesis of methanol from CO2 that could provide a viable path toward carbon neutrality and environmental sustainability. [ABSTRACT FROM AUTHOR]

In order to determine the most suitable turbulence model for studying the aerodynamic performance of bus, the effects of different turbulence models on the aerodynamic characteristics of bus were investigated. A comparative analysis was conducted on five turbulence models (IDDES, DDES, DES, LES, URANS). The pressure distribution on the cross section at x=0 and y=0 is also analyzed for each model. The results reveal that IDDES accurately captures the negative pressure at the rear of the bus and predicts the pressure gradients more effectively than other models. IDDES also captures more vortices at the head of the bus and predicts the wake flow more widely than other models. DDES has obvious shedding phenomenon in the wake flow, while IDDES provides a relatively smooth airflow trajectory, but its prediction of airflow trajectory at a distance is less clear. Through quantitative and qualitative analyses of the aerodynamic characteristics of bus under different turbulence models, it can be concluded that IDDES is the most suitable turbulence model to study the aerodynamic characteristics of bus. [ABSTRACT FROM AUTHOR]

Rational: Small bowel Crohn's disease (SBCD) is a common site of Crohn's disease (CD). However, owing to the anatomical characteristics of the small bowel and the limitations of traditional examination methods, the detection and diagnosis of SBCD remain difficult. Gastroenterologists and anorectal surgeons should pay more attention to improving the early diagnosis rate, so as to improve the prognosis of patients and reduce the probability of surgery due to complications., Patient Concerns: Here, we presented a case of a young male with severe localized pain in the right kidney area and fever but no weight loss or diarrhea, who had a history of perianal abscess surgery 7 years ago and an elevated platelet count reviewing his previous medical examination report., Diagnoses: SBCD was not diagnosed until complications of intestinal fistula developed 7 years after perianal abscess surgery., Interventions: Anti-infection treatment was administered due to elevated inflammatory markers and evidence of infection on computed tomography scan, and exclusive enteral nutrition (EEN) was then performed because of the diagnosis of SBCD. Although the infection was absorbed by the treatment with EEN, a laparoscopic modified partial enterectomy was finally performed due to the complication of intestinal fistula., Outcomes: The patient was discharged on the seventh postoperative day without postoperative complications and started biologic therapy 2 weeks after surgery because he had high-risk factors for postoperative recurrence. The pathological report revealed the involvement of the ileum in CD, and confirmed the existence of the intestinal fistula., Lessons: Gastroenterologists and anorectal surgeons should be aware that perianal abscess could be the first manifestation of SBCD; even if typical CD manifestations are absent, proper further examinations are necessary based on the comprehensive analysis of clinical data of patients. In addition, the platelet count deserves attention in patients with potentially possible CD. More importantly, it is important to emphasize the importance of EEN in adult CD patients., Competing Interests: The authors have no funding and conflicts of interest to disclose., (Copyright © 2024 the Author(s). Published by Wolters Kluwer Health, Inc.)

Lithium-ion batteries using quasi-solid gel electrolytes (QSEs) have gained increasing interest due to their enhanced safety features. However, their commercial viability is hindered by low ionic conductivity and poor solid-solid contact interfaces. In this study, a QSE synthesized by in situ polymerizing methyl methacrylate (MMA) in 1,2-dimethoxyethane (DME)-based electrolyte is introduced, which exhibits remarkable performance in high-loading graphite||LiNi 0.8 Co 0.1 Mn 0.1 O 2 (NCM811) pouch cells. Owing to the unique solvent-lacking solvation structure, the graphite exfoliation caused by the well-known solvent co-intercalation is prohibited, and this unprecedented phenomenon is found to be universal for other graphite-unfriendly solvents. The high ionic conductivity and great interfacial contact provided by DME enable the quasi-solid graphite||NCM811 pouch cell to demonstrate superior C-rate capability even at a high cathode mass loading (17.5 mg cm -2 ), surpassing liquid carbonate electrolyte cells. Meanwhile, the optimized QSE based on carbonates exhibits excellent cycle life (92.4% capacity retention after 1700 cycles at 0.5C/0.5C) and reliable safety under harsh conditions. It also outperforms liquid electrolytes in other high-energy-density batteries with larger volume change. These findings elucidate the polymer's pivotal role in QSEs, offering new insights for advancing quasi-solid-state battery commercialization., (© 2024 The Author(s). Advanced Materials published by Wiley‐VCH GmbH.)

Robust sampling methods are foundational to inferences using phylogenies. Yet the impact of using contact tracing, a type of non-uniform sampling used in public health applications such as infectious disease outbreak investigations, has not been investigated in the molecular epidemiology field. To understand how contact tracing influences a recovered phylogeny, we developed a new simulation tool called SEEPS (Sequence Evolution and Epidemiological Process Simulator) that allows for the simulation of contact tracing and the resulting transmission tree, pathogen phylogeny, and corresponding virus genetic sequences. Importantly, SEEPS takes within-host evolution into account when generating pathogen phylogenies and sequences from transmission histories. Using SEEPS, we demonstrate that contact tracing can significantly impact the structure of the resulting tree, as described by popular tree statistics. Contact tracing generates phylogenies that are less balanced than the underlying transmission process, less representative of the larger epidemiological process, and affects the internal/external branch length ratios that characterize specific epidemiological scenarios. We also examined real data from a 2007-2008 Swedish HIV-1 outbreak and the broader 1998-2010 European HIV-1 epidemic to highlight the differences in contact tracing and expected phylogenies. Aided by SEEPS, we show that the data collection of the Swedish outbreak was strongly influenced by contact tracing even after downsampling, while the broader European Union epidemic showed little evidence of universal contact tracing, agreeing with the known epidemiological information about sampling and spread. Overall, our results highlight the importance of including possible non-uniform sampling schemes when examining phylogenetic trees. For that, SEEPS serves as a useful tool to evaluate such impacts, thereby facilitating better phylogenetic inferences of the characteristics of a disease outbreak. SEEPS is available at github.com/MolEvolEpid/SEEPS.

Diabetic foot ulcers (DFUs) are chronic wounds and one of the most common complications of diabetes, imposing significant physical and mental burdens on patients due to their poor prognosis and treatment efficacy. Adipose-derived stem cells (ADSCs) have been proven to promote wound healing, with studies increasingly attributing these beneficial effects to their paracrine actions. Consequently, research on ADSC secretome as a novel and promising alternative for DFU treatment has been extensively conducted. This article provides a comprehensive review of the mechanisms underlying refractory DFU wounds, the secretome of ADSCs, and its role in promoting wound healing in diabetes foot ulcers. And the review aims to provide reliable evidence for the clinical application of ADSC secretome in the treatment of refractory DFU wounds., (© 2024. The Author(s).)

Mixed-lineage kinase 3 (MLK3) is a serine/threonine kinase of the MAPK Kinase kinase (MAP3K) family that plays critical roles in various biological processes, including cancer. Upon activation, MLK3 differentially activates downstream MAPKs, such as JNK, p38, and ERK. In addition, it regulates various non-canonical signaling pathways, such as β-catenin, AMPK, Pin1, and PAK1, to regulate cell proliferation, apoptosis, invasion, and metastasis. Recent studies have also uncovered other potentially diverse roles of MLK3 in malignancy, which include metabolic reprogramming, cancer-associated inflammation, and evasion of cancer-related immune surveillance. The role of MLK3 in cancer is complex and cancer-specific, and an understanding of its function at the molecular level aligned specifically with the cancer hallmarks will have profound therapeutic implications for diagnosing and treating MLK3-dependent cancers. This review summarizes the current knowledge about the effect of MLK3 on the hallmarks of cancer, providing insights into its potential as a promising anticancer drug target., Competing Interests: Declaration of competing interest The authors declare that they have no competing interests., (Published by Elsevier B.V.)

The conversion of CO 2 into liquid fuels, using only sunlight and water, offers a promising path to carbon neutrality. An outstanding challenge is to achieve high efficiency and product selectivity. Here, we introduce a wireless photocatalytic architecture for conversion of CO 2 and water into methanol and oxygen. The catalytic material consists of semiconducting nanowires decorated with core-shell nanoparticles, with a copper-rhodium core and a chromium oxide shell. The Rh/CrOOH interface provides a unidirectional channel for proton reduction, enabling hydrogen spillover at the core-shell interface. The vectorial transfer of protons, electrons, and hydrogen atoms allows for switching the mechanism of CO 2 reduction from a proton-coupled electron transfer pathway in aqueous solution to hydrogenation of CO 2 with a solar-to-methanol efficiency of 0.22%. The reported findings demonstrate a highly efficient, stable, and scalable wireless system for synthesis of methanol from CO 2 that could provide a viable path toward carbon neutrality and environmental sustainability., Competing Interests: Competing interests statement:Some IP related to this work has been licensed to NS Nanotech, Inc. and NX Fuels, Inc., which were co-founded by Z.M. The University of Michigan and Mi have a financial interest in these companies.

Most people living with HIV-1 experience rapid viral rebound once antiretroviral therapy is interrupted; however, a small fraction remain in viral remission for an extended duration. Understanding the factors that determine whether viral rebound is likely after treatment interruption can enable the development of optimal treatment regimens and therapeutic interventions to potentially achieve a functional cure for HIV-1. We built upon the theoretical framework proposed by Conway and Perelson to construct dynamic models of virus-immune interactions to study factors that influence viral rebound dynamics. We evaluated these models using viral load data from 24 individuals following antiretroviral therapy interruption. The best-performing model accurately captures the heterogeneity of viral dynamics and highlights the importance of the effector cell expansion rate. Our results show that post-treatment controllers and non-controllers can be distinguished based on the effector cell expansion rate in our models. Furthermore, these results demonstrate the potential of using dynamic models incorporating an effector cell response to understand early viral rebound dynamics post-antiretroviral therapy interruption., Competing Interests: JMC is a consultant for Excision Biotherapeutics and Merck. The other authors declare no competing interest., (Copyright: This is an open access article, free of all copyright, and may be freely reproduced, distributed, transmitted, modified, built upon, or otherwise used by anyone for any lawful purpose. The work is made available under the Creative Commons CC0 public domain dedication.)

Multiplexed in situ RNA imaging offers new opportunities for gene expression profiling by providing high-throughput spatial information. In this work, we present a cyclic combinatorial fluorescent in situ hybridization (combFISH) assay to achieve multiplexed detection of RNA in cell cultures and tissues. Specifically, multiplexing is achieved through cyclic interrogation of barcode sequences on the rolling circle amplicons generated from the padlock probe assay by using sets of combinatorial detection probes. Theoretically, combFISH can detect 64 genes in three hybridization cycles by combinatorial barcoding using 12 fluorescently labeled detection probes. Our method eliminates sequencing-by-ligation (SBL) chemistry in the in situ sequencing protocol and directly uses RNA as targets for ligation, making it more straightforward. We showed that our method works in fresh-frozen and formalin-fixed paraffin-embedded tissue sections. With its straightforward protocols, we expect our method to be adopted by the scientific community and extended to clinical settings., (© 2024. The Author(s), under exclusive licence to Springer-Verlag GmbH, DE part of Springer Nature.)

An important aspect of how viruses spread and infect is the viral burst size, or the number of new viruses produced by each infected cell. Surprisingly, this value remains poorly characterized for influenza A virus (IAV), commonly known as the flu. In this study, we screened tens of thousands of cells using a microfluidic method called droplet quantitative PCR (dqPCR). The high-throughput capability of dqPCR enabled the measurement of a large population of infected cells producing progeny virus. By measuring the fully assembled and successfully released viruses from these infected cells, we discover that the viral burst sizes for both the seasonal H3N2 and the 2009 pandemic H1N1 strains vary significantly, with H3N2 ranging from 101 to 104 viruses per cell, and H1N1 ranging from 101 to 103 viruses per cell. Some infected cells produce average numbers of new viruses, while others generate extensive number of viruses. In fact, we find that only 10% of the single-cell infections are responsible for creating a significant portion of all the viruses. This small fraction produced approximately 60% of new viruses for H3N2 and 40% for H1N1. On average, each infected cell of the H3N2 flu strain produced 709 new viruses, whereas for H1N1, each infected cell produced 358 viruses. This novel method reveals insights into the flu virus and can lead to improved strategies for managing and preventing the spread of viruses., Competing Interests: The authors have declared that no competing interests exist., (Copyright: This is an open access article, free of all copyright, and may be freely reproduced, distributed, transmitted, modified, built upon, or otherwise used by anyone for any lawful purpose. The work is made available under the Creative Commons CC0 public domain dedication.)

Advanced hepatocellular carcinoma (HCC) is a lethal disease, with limited therapeutic options. Mixed Lineage Kinase 3 (MLK3) is a key regulator of liver diseases, although its role in HCC remains unclear. Analysis of TCGA databases suggested elevated MAP3K11 (MLK3 gene) expression, and TMA studies showed higher MLK3 activation in human HCCs. To understand MLK3's role in HCC, we utlized carcinogen-induced HCC model and compared between wild-type and MLK3 knockout (MLK3 -/- ) mice. Our studies showed that MLK3 kinase activity is upregulated in HCC, and MLK3 deficiency alleviates HCC progression. MLK3 deficiency reduced proliferation in vivo and MLK3 inhibition reduced proliferation and colony formation in vitro. To obtain further insight into the mechanism and identify newer targets mediating MLK3-induced HCCs, RNA-sequencing analysis was performed. These showed that MLK3 deficiency modulates various gene signatures, including EMT, and reduces TGFB1&2 expressions. HCC cells overexpressing MLK3 promoted EMT via autocrine TGFβ signaling. Moreover, MLK3 deficiency attenuated activated hepatic stellate cell (HSC) signature, which is increased in wild-type. Interestingly, MLK3 promotes HSC activation via paracrine TGFβ signaling. These findings reveal TGFβ playing a key role at different steps of HCC, downstream of MLK3, implying MLK3-TGFβ axis to be an ideal drug target for advanced HCC management., (© 2024. The Author(s), under exclusive licence to Springer Nature Limited.)

Fibroblast growth factor receptor 2 (FGFR2) represents an appealing therapeutic target for multiple cancers, yet no selective FGFR2 inhibitors have been approved for clinical use to date. Here, we report the discovery of a series of new selective, irreversible FGFR2 inhibitors. The representative compound LHQ490 potently inhibited FGFR2 kinase activity with an IC 50 of 5.2 nM, and was >61-, >34-, and >293-fold selective against FGFR1, FGFR3, and FGFR4, respectively. LHQ490 also exhibited high selectivity in a panel of 416 kinases. Cell-based studies revealed that LHQ490 efficiently suppressed the proliferation of BaF3-FGFR2 cells with an IC 50 value of 1.4 nM, and displayed >70- and >714-fold selectivity against BaF3-FGFR1 and the parental BaF3 cells, respectively. More importantly, LHQ490 potently suppressed the FGFR2 signaling pathways, selectively inhibited FGFR2-driven cancer cell proliferation, and induced apoptosis of FGFR2-driven cancer cells. Taken together, this study provides a potent and highly selective FGFR2 inhibitor for further development of FGFR2-targeted therapeutic agents., Competing Interests: Declaration of competing interest The authors declare no competing financial interest., (Copyright © 2024 Elsevier Masson SAS. All rights reserved.)

Polymer/ceramic-based composite solid electrolytes (CSE) are promising candidates for all-solid-state lithium metal batteries (SLBs), benefiting from the combined mechanical robustness of polymeric electrolytes and the high ionic conductivity of ceramic electrolytes. However, the interfacial instability and poorly understood interphases of CSE hinder their application in high-voltage SLBs. Herein, a simple but effective CSE that stabilizes high-voltage SLBs by forming multiple intermolecular coordination interactions between polyester and ceramic electrolytes is discovered. The multiple coordination between the carbonyl groups in poly(ε-caprolactone) and the fluorosulfonyl groups in anions with Li 6.5 La 3 Zr 1.5 Ta 0.5 O 12 nanoparticles is directly visualized by cryogenic transmission electron microscopy and further confirmed by theoretical calculation. Importantly, the multiple coordination in CSE not only prevents the continuous decomposition of polymer skeleton by shielding the vulnerable carbonyl sites but also establishes stable inorganic-rich interphases through preferential decomposition of anions. The stable CSE and its inorganic-rich interphases enable Li||Li symmetric cells with an exceptional lifespan of over 4800 h without dendritic shorting at 0.1 mA cm -2 . Moreover, the high-voltage SLB with LiNi 0.5 Co 0.2 Mn 0.3 O 2 cathode displays excellent cycling stability over 1100 cycles at a 1C charge/discharge rate. This work reveals the underlying mechanism behind the excellent stability of coordinating composite electrolytes and interfaces in high-voltage SLBs., (© 2024 Wiley‐VCH GmbH.)

Air pollution is a primary concern, causing around 7 million premature deaths annually, with traffic-related sources contributing 23 %-45 % of emissions. While several studies have surveyed vehicle emission models, they are either outdated or focus on specific data-driven models. This paper systematically reviews vehicle emission prediction models, comparing traditional approaches with data-driven emission models. The traditional emission models can be divided into average-speed, modal, and other models, noting their reliance on empirical assumptions and parameters that may not be universally applicable. In contrast, we delve into data-driven models utilizing dynamometer and on-road test data for time-series and spatial-temporal predictions. The application of these models is discussed across various scenarios, highlighting the progress and gap. We observed that traditional models, primarily estimating total traffic emissions in study regions, lack micro-level detail crucial for tailored decisions. The direct link between road emission model accuracy and input data quality poses challenges in disaggregating on-road vehicle emission inventories. Due to unique transportation instruments, traffic fleet components, and patterns, exploring the effects of emission-reduction policies in specific cities or regions is urgent. Vehicle characteristics, environmental conditions, traffic scenarios, and prediction scales are common effect factors, while instantaneous driving profiles prove effective in model calibration. In data-driven models, ANN outperforms in estimating emissions and performance of low-power diesel engines with errors not exceeding 5 %. However, no single data-driven method performed excellently in predicting all pollutants. Besides, integrated methods utilizing LSTM, GRU, and RNN outperform individual models. To enhance prediction accuracy considering the inherent connectivity of road networks and spatiotemporal variation patterns of vehicle emissions, GCN is an emerging approach for capturing spatial-temporal relationships based on remote sensing data. Moreover, limited data-driven studies have been performed to forecast particle matter emissions, the main contributors to urban pollution, calling for more attention for future research., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier B.V. All rights reserved.)

Loss of refreshment in nucleus pulposus (NP) cellularity leads to intervertebral disc (IVD) degeneration. Nevertheless, the cellular sequence of NP cell differentiation remains unclear, although an increasing body of literature has identified markers of NP progenitor cells (NPPCs). Notably, due to their fragility, the physical enrichment of NP-derived cells has limited conventional transcriptomic approaches in multiple studies. To overcome this limitation, a spatially resolved transcriptional atlas of the mouse IVD is generated via the 10x Genomics Visium platform dividing NP spots into two clusters. Based on this, most reported NPPC-markers, including Cathepsin K (Ctsk), are rare and predominantly located within the NP-outer subset. Cell lineage tracing further evidence that a small number of Ctsk-expressing cells generate the entire adult NP tissue. In contrast, Tie2, which has long suggested labeling NPPCs, is actually neither expressed in NP subsets nor labels NPPCs and their descendants in mouse models; consistent with this, an in situ sequencing (ISS) analysis validated the absence of Tie2 in NP tissue. Similarly, no Tie2-cre-mediated labeling of NPPCs is observed in an IVD degenerative mouse model. Altogether, in this study, the first spatial transcriptomic map of the IVD is established, thereby providing a public resource for bone biology., (© 2024 The Authors. Advanced Science published by Wiley‐VCH GmbH.)

Background: Acne vulgaris is a widespread chronic inflammatory dermatological condition. The precise molecular and genetic mechanisms of its pathogenesis remain incompletely understood. This research synthesizes existing databases, targeting a comprehensive exploration of core genetic markers., Methods: Gene expression datasets (GSE6475, GSE108110, and GSE53795) were retrieved from the GEO. Differentially expressed genes (DEGs) were identified using the limma package. Enrichment analyses were conducted using GSVA for pathway assessment and clusterProfiler for GO and KEGG analyses. PPI networks and immune cell infiltration were analyzed using the STRING database and ssGSEA, respectively. We investigated the correlation between hub gene biomarkers and immune cell infiltration using Spearman's rank analysis. ROC curve analysis validated the hub genes' diagnostic accuracy. miRNet, TarBase v8.0, and ChEA3 identified miRNA/transcription factor-gene interactions, while DrugBank delineated drug-gene interactions. Experiments utilized HaCaT cells stimulated with Propionibacterium acnes, treated with retinoic acid and methotrexate, and evaluated using RT-qPCR, ELISA, western blot, lentiviral transduction, CCK-8, wound-healing, and transwell assays., Results: There were 104 genes with consistent differences across the three datasets of paired acne and normal skin. Functional analyses emphasized the significant enrichment of these DEGs in immune-related pathways. PPI network analysis pinpointed hub genes PTPRC, CXCL8, ITGB2, and MMP9 as central players in acne pathogenesis. Elevated levels of specific immune cell infiltration in acne lesions corroborated the inflammatory nature of the disease. ROC curve analysis identified the acne diagnostic potential of four hub genes. Key miRNAs, particularly hsa-mir-124-3p, and central transcription factors like TFEC were noted as significant regulators. In vitro validation using HaCaT cells confirmed the upregulation of hub genes following Propionibacterium acnes exposure, while CXCL8 knockdown reduced pro-inflammatory cytokines, cell proliferation, and migration. DrugBank insights led to the exploration of retinoic acid and methotrexate, both of which mitigated gene expression upsurge and inflammatory mediator secretion., Conclusion: This comprehensive study elucidated pivotal genes associated with acne pathogenesis, notably PTPRC, CXCL8, ITGB2, and MMP9. The findings underscore potential biomarkers, therapeutic targets, and the therapeutic potential of agents like retinoic acid and methotrexate. The congruence between bioinformatics and experimental validations suggests promising avenues for personalized acne treatments., (© 2024 The Authors. Journal of Cosmetic Dermatology published by Wiley Periodicals LLC.)

To mitigate the loss of lives during the COVID-19 pandemic, emergency use authorization was given to several anti-SARS-CoV-2 monoclonal antibody (mAb) therapies for the treatment of mild-to-moderate COVID-19 in patients with a high risk of progressing to severe disease. Monoclonal antibodies used to treat SARS-CoV-2 target the spike protein of the virus and block its ability to enter and infect target cells. Monoclonal antibody therapy can thus accelerate the decline in viral load and lower hospitalization rates among high-risk patients with variants susceptible to mAb therapy. However, viral resistance has been observed, in some cases leading to a transient viral rebound that can be as large as 3-4 orders of magnitude. As mAbs represent a proven treatment choice for SARS-CoV-2 and other viral infections, evaluation of treatment-emergent mAb resistance can help uncover underlying pathobiology of SARS-CoV-2 infection and may also help in the development of the next generation of mAb therapies. Although resistance can be expected, the large rebounds observed are much more difficult to explain. We hypothesize replenishment of target cells is necessary to generate the high transient viral rebound. Thus, we formulated two models with different mechanisms for target cell replenishment (homeostatic proliferation and return from an innate immune response antiviral state) and fit them to data from persons with SARS-CoV-2 treated with a mAb. We showed that both models can explain the emergence of resistant virus associated with high transient viral rebounds. We found that variations in the target cell supply rate and adaptive immunity parameters have a strong impact on the magnitude or observability of the viral rebound associated with the emergence of resistant virus. Both variations in target cell supply rate and adaptive immunity parameters may explain why only some individuals develop observable transient resistant viral rebound. Our study highlights the conditions that can lead to resistance and subsequent viral rebound in mAb treatments during acute infection., Competing Interests: We have read the journal’s policy and the authors of this manuscript have the following competing interests: K.W.C. has received research funding to her institution from Merck Sharp & Dohme and consulted for Pardes Biosciences. D.M.S. has consulted for the following companies Fluxergy, Kiadis, Linear Therapies, Matrix BioMed, Lucira, VxBiosciences, Model Medicines, Bayer Pharmaceuticals, and Evidera. E.S.D. has consulted for Gilead, Merck, ViiV and Theratechnologies and received research funding to his institution from Gilead and ViiV. D.A.W. has consulted for Gilead Sciences, ViiV Healthcare, Janssen Pharmaceuticals, and Theratechnologies, and has university grant funding from Gilead Sciences, ViiV Healthcare, and Merck and Co. J. J. E. is on the DMC for Adagio/Invyvid and has consulted for Gilead Sciences and Merck & Co. J. S. C. has consulted for Merck & Co., J.Z.L. has consulted for Abbvie. The other authors have declared that no competing interests exist., (Copyright: This is an open access article, free of all copyright, and may be freely reproduced, distributed, transmitted, modified, built upon, or otherwise used by anyone for any lawful purpose. The work is made available under the Creative Commons CC0 public domain dedication.)

Mathematical models of viral infection have been developed, fitted to data, and provide insight into disease pathogenesis for multiple agents that cause chronic infection, including HIV, hepatitis C, and B virus. However, for agents that cause acute infections or during the acute stage of agents that cause chronic infections, viral load data are often collected after symptoms develop, usually around or after the peak viral load. Consequently, we frequently lack data in the initial phase of viral growth, i.e., when pre-symptomatic transmission events occur. Missing data may make estimating the time of infection, the infectious period, and parameters in viral dynamic models, such as the cell infection rate, difficult. However, having extra information, such as the average time to peak viral load, may improve the robustness of the estimation. Here, we evaluated the robustness of estimates of key model parameters when viral load data prior to the viral load peak is missing, when we know the values of some parameters and/or the time from infection to peak viral load. Although estimates of the time of infection are sensitive to the quality and amount of available data, particularly pre-peak, other parameters important in understanding disease pathogenesis, such as the loss rate of infected cells, are less sensitive. Viral infectivity and the viral production rate are key parameters affecting the robustness of data fits. Fixing their values to literature values can help estimate the remaining model parameters when pre-peak data is missing or limited. We find a lack of data in the pre-peak growth phase underestimates the time to peak viral load by several days, leading to a shorter predicted growth phase. On the other hand, knowing the time of infection (e.g., from epidemiological data) and fixing it results in good estimates of dynamical parameters even in the absence of early data. While we provide ways to approximate model parameters in the absence of early viral load data, our results also suggest that these data, when available, are needed to estimate model parameters more precisely., Competing Interests: The authors have declared that no competing interests exist., (Copyright: This is an open access article, free of all copyright, and may be freely reproduced, distributed, transmitted, modified, built upon, or otherwise used by anyone for any lawful purpose. The work is made available under the Creative Commons CC0 public domain dedication.)

Endogenous retroviruses (ERVs) are ancient retroviral remnants integrated in host genomes, and commonly deleted through unequal homologous recombination, leaving solitary long terminal repeats (solo-LTRs). This study, analysing the genomes of 362 bird species and their reptilian and mammalian outgroups, reveals an unusually higher level of solo-LTRs formation in birds, indicating evolutionary forces might have purged ERVs during evolution. Strikingly in the order Passeriformes, and especially the parvorder Passerida, endogenous retrovirus K (ERVK) solo-LTRs showed bursts of formation and recurrent accumulations coinciding with speciation events over past 22 million years. Moreover, our results indicate that the ongoing expansion of ERVK solo-LTRs in these bird species, marked by high transcriptional activity of ERVK retroviral genes in reproductive organs, caused variation of solo-LTRs between individual zebra finches. We experimentally demonstrated that cis-regulatory activity of recently evolved ERVK solo-LTRs may significantly increase the expression level of ITGA2 in the brain of zebra finches compared to chickens. These findings suggest that ERVK solo-LTRs expansion may introduce novel genomic sequences acting as cis-regulatory elements and contribute to adaptive evolution. Overall, our results underscore that the residual sequences of ancient retroviruses could influence the adaptive diversification of species by regulating host gene expression., (© 2024. The Author(s).)

Human immunodeficiency virus type 1 typically requires a high density of CD4 for efficient entry as a mechanism to target CD4+ T cells (T-tropic), with CCR5 being used most often as the coreceptor. When target T cells are limiting, the virus can evolve to infect cells with a low density of CD4 such as macrophages (M-tropic). The entry phenotype is known to be encoded in the viral Env protein on the surface of the virus particle. Using data showing a dose response for infectivity based on CD4 surface density, we built a model consistent with T-tropic viruses requiring multiple CD4 molecules to mediate infection, whereas M-tropic viruses can infect cells using a single CD4 receptor molecule interaction. We also found that T-tropic viruses bound to the surface of cells with a low density of CD4 are released more slowly than M-tropic viruses which we modeled to be due to multiple interactions of the T-tropic virus with multiple CD4 molecules to allow the initial stable binding. Finally, we found that some M-tropic Env proteins, as the gp120 subunit, possess an enhanced affinity for CD4 compared with their T-tropic pair, indicating that the evolution of macrophage tropism can be reflected both in the closed Env trimer conformation on the virion surface and, in some cases, also in the open confirmation of gp120 Env. Collectively, these studies reveal differences in the stoichiometry of interaction of T-tropic and M-tropic viruses with CD4 and start to identify the basis of binding differences at the biochemical level., Importance: Human immunodeficiency virus type 1 normally targets CD4+ T cells for viral replication. When T cells are limiting, the virus can evolve to infect myeloid cells. The evolutionary step involves a change from requiring a high surface density of CD4 for entry to being able to infect cells with a low density of CD4, as is found on myeloid lineage cells such as macrophage and microglia. Viruses able to infect macrophages efficiently are most often found in the CNS late in the disease course, and such viruses may contribute to neurocognitive impairment. Here, we examine the CD4 binding properties of the viral Env protein to explore these two different entry phenotypes., Competing Interests: The authors declare no conflict of interest.

Background: The histone deacetylase inhibitor vorinostat (VOR) can reverse human immunodeficiency virus type 1 (HIV-1) latency in vivo and allow T cells to clear infected cells in vitro. HIV-specific T cells (HXTCs) can be expanded ex vivo and have been safely administered to people with HIV (PWH) on antiretroviral therapy., Methods: Six PWH received infusions of 2 × 107 HXTCs/m² with VOR 400 mg, and 3 PWH received infusions of 10 × 107 HXTCs/m² with VOR. The frequency of persistent HIV by multiple assays including quantitative viral outgrowth assay (QVOA) of resting CD4+ T cells was measured before and after study therapy., Results: VOR and HXTCs were safe, and biomarkers of serial VOR effect were detected, but enhanced antiviral activity in circulating cells was not evident. After 2 × 107 HXTCs/m² with VOR, 1 of 6 PWH exhibited a decrease in QVOA, and all 3 PWH exhibited such declines after 10 × 107 HXTCs/m² and VOR. However, most declines did not exceed the 6-fold threshold needed to definitively attribute decline to the study intervention., Conclusions: These modest effects provide support for the strategy of HIV latency reversal and reservoir clearance, but more effective interventions are needed to yield the profound depletion of persistent HIV likely to yield clinical benefit. Clinical Trials Registration. NCT03212989., Competing Interests: Potential conflicts of interest. C. M. B. is a scientific co-founder and scientific advisory board member for Catamaran Bio and Mana Therapeutics; serves on the board of directors of Cabaletta Bio; has stock in Neximmune and Repertoire Immune Medicine; serves on the data and safety monitoring board for SOBI; and has served on advisory boards for BMS, Roche, and Pfizer. D. M. M. has provided consultancy to ViiV Healthcare outside of this work and owns common stock in Gilead Sciences. P. J. H. is a co-founder and serves on the board of directors of Mana Therapeutics and is an advisor to Cellenkos, Cellevolve, Discovery Life Sciences, Capsida, and MicroFluidX. All other authors report no potential conflicts. All authors have submitted the ICMJE Form for Disclosure of Potential Conflicts of Interest. Conflicts that the editors consider relevant to the content of the manuscript have been disclosed., (© The Author(s) 2024. Published by Oxford University Press on behalf of Infectious Diseases Society of America. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)

Spatial transcriptomics (ST) is featured by high-throughput gene expression profiling within their native cell and tissue context, offering a means to investigate gene regulatory networks in tissue microenvironment. In situ sequencing (ISS) is an imaging-based ST technology that simultaneously detects hundreds to thousands of genes at subcellular resolution. As a highly reproducible and robust technique, ISS has been widely adapted and undergone a series of technical iterations. As the interest in ISS-based spatial transcriptomic analysis grows, scalable and integrated data analysis workflows are needed to facilitate the applications of ISS in different research fields. This review presents the state-of-the-art bioinformatic toolkits for ISS data analysis, which covers the upstream and downstream analysis workflows, including image analysis, cell segmentation, clustering, functional enrichment, detection of spatially variable genes and cell clusters, spatial cell-cell interactions, and trajectory inference. To assist the community in choosing the right tools for their research, the application of each tool and its compatibility with ISS data are reviewed in detailed. Finally, future perspectives and challenges concerning how to integrate heterogeneous tools into a user-friendly analysis pipeline are discussed. This article is categorized under: RNA Methods > RNA Analyses In Vitro and In Silico., (© 2024 Wiley Periodicals LLC.)

We present a combined amplification-based single-molecule fluorescence in situ hybridization and immunofluorescence (asmFISH-IF) method for the detection of multiple RNAs and proteins simultaneously in cells and formaldehyde-fixed and paraffin-embedded tissue sections. We showed that performing asmFISH before immunofluorescence gives a better IF signal than the opposite. Our asmFISH-IF method could help study the interplay of RNA and protein, helping to understand their functions., Competing Interests: Declaration of competing interest The authors declare no competing interests., (Copyright © 2024 Elsevier Inc. All rights reserved.)

Background: Hematoma expansion (HE) is common in patients with intracerebral hemorrhage (ICH) and associated with a worse outcome. Imaging makers and shorter time from symptom onset are both associated with HE, but prognostic scores based on these parameters individually have not been satisfactory. We hypothesized that a score including both imaging markers of expansion, and time of onset, would improve prediction., Methods: Patients with supratentorial ICH within 6 h after onset were consecutively recruited from six centers between January 2018 and August 2022. Three markers were used: hypodensities, the blend sign, and the island sign. We first defined frequency of imaging markers (FIM) as the relationship between the number of imaging markers and onset-to-CT time (OCT). The time-adjusted FIM was defined as the ratio of the number of imaging markers to the onset-to-initial imaging time. Multivariate analysis was performed to determine the relationship between FIM and HE. Receiver operating curve analysis was used to identify potential threshold values of FIM that optimally predict HE. In addition, the sensitivity, specificity, positive and negative predictive values (PPVs and NPVs), and the area under the curve (AUC) of the optimal cut-off in predicting HE were calculated., Results: In total, 1488 patients were eligible for inclusion, of whom 418 had incident HE. Multivariate analysis showed that age, male sex, baseline Glasgow Coma Scale score, presence of intraventricular hemorrhage, and FIM were independent predictors of HE (odds ratio (OR) = 0.98, 95% confidence interval (CI) = 0.97-0.99; OR = 1.73, 95% CI = 1.28-2.35; OR = 0.87, 95% CI = 0.83-0.92; OR = 0.42, 95% CI = 0.28-0.62; OR = 7.82, 95% CI = 5.86-10.42, respectively). The optimal cut-off point for FIM in predicting HE was 0.63, with sensitivity, specificity, PPV, NPV, and AUC values of 0.69, 0.89, 0.71, 0.88, and 0.83, respectively., Conclusion: The FIM adjusted for time since symptom onset is a significant predictor of HE. Its use may allow improved prediction of those patients with ICH who develop HE, and the score may be clinically applicable in the management of patients with ICH., Competing Interests: Declaration of conflicting interestsThe author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

RNA in situ hybridization reveals the abundance and location of gene expression in cells or tissues, providing a technical basis for the clinical diagnosis of diseases. In this chapter, we show a "V" shape probe-mediated single-molecule chromogenic in situ hybridization (vsmCISH) technique for bright-field visualization of individual RNA molecules. In our method, several pairs of target hybridization probes are hybridized to RNA molecules and each probe pair forms a "V" shape overhang. The overhang oligonucleotides then mediated the proximity ligation to form DNA circles, followed by rolling circle amplification for signal enhancement and enzyme-catalyzed chromogenic reaction-based readout. The colorimetric assay avoids problems such as photobleaching and autofluorescence of current fluorescent in situ hybridization-based single-molecule RNA detection techniques. Furthermore, the relatively straightforward protocol makes the method useful for biological research and clinical diagnosis applications., (© 2024. The Author(s), under exclusive license to Springer Science+Business Media, LLC, part of Springer Nature.)

With recent deep learning based approaches showing promising results in removing noise from images, the best denoising performance has been reported in a supervised learning setup that requires a large set of paired noisy images and ground truth data for training. The strong data requirement can be mitigated by unsupervised learning techniques, however, accurate modelling of images or noise variances is still crucial for high-quality solutions. The learning problem is ill-posed for unknown noise distributions. This paper investigates the tasks of image denoising and noise variance estimation in a single, joint learning framework. To address the ill-posedness of the problem, we present deep variation prior (DVP), which states that the variation of a properly learnt denoiser with respect to the change of noise satisfies some smoothness properties, as a key criterion for good denoisers. Building upon DVP and under the assumption that the noise is zero mean and pixel-wise independent conditioned on the image, an unsupervised deep learning framework, that simultaneously learns a denoiser and estimates noise variances, is developed. Our method does not require any clean training images or an external step of noise estimation, and instead, approximates the minimum mean squared error denoisers using only a set of noisy images. With the two underlying tasks being considered in a single framework, we allow them to be optimised for each other. The experimental results show a denoising quality comparable to that of supervised learning and accurate noise variance estimates.