Africa-specific human genetic variation near CHD1L associates with HIV-1 load.

HIV-1 remains a global health crisis1, highlighting the need to identify new targets for therapies. Here, given the disproportionate HIV-1 burden and marked human genome diversity in Africa2, we assessed the genetic determinants of control of set-point viral load in 3,879 people of African ancestries living with HIV-1 participating in the international collaboration for the genomics of HIV3. We identify a previously undescribed association signal on chromosome 1 where the peak variant associates with an approximately 0.3 log10-transformed copies per ml lower set-point viral load per minor allele copy and is specific to populations of African descent. The top associated variant is intergenic and lies between a long intergenic non-coding RNA (LINC00624) and the coding gene CHD1L, which encodes a helicase that is involved in DNA repair4. Infection assays in iPS cell-derived macrophages and other immortalized cell lines showed increased HIV-1 replication in CHD1L-knockdown and CHD1L-knockout cells. We provide evidence from population genetic studies that Africa-specific genetic variation near CHD1L associates with HIV replication in vivo. Although experimental studies suggest that CHD1L is able to limit HIV infection in some cell types in vitro, further investigation is required to understand the mechanisms underlying our observations, including any potential indirect effects of CHD1L on HIV spread in vivo that our cell-based assays cannot recapitulate.

Hairpin-Empowered Invasive Reaction Combined with Catalytic Hairpin Assembly Cascade Amplification for the Specific Detection of Single-Nucleotide Polymorphisms.

Single-nucleotide polymorphism (SNP) is widely used in the study of disease-related genes and in the genetic study of animal and plant strains. Therefore, SNP detection is crucial for biomedical diagnosis and treatment as well as for molecular design breeding of animals and plants. In this regard, this article describes a novel technique for detecting SNP using flap endonuclease 1 (FEN 1) as a specific recognition element and catalytic hairpin assembly (CHA) cascade reaction as a signal amplification strategy. The mutant target (MT) was hybridized with a biotin-modified upstream probe and hairpin-type downstream probe (DP) to form a specific three-base overlapping structure. Then, FEN 1 was employed for three-base overlapping structure-specific recognition, namely, the precise SNP site identification and the 5' flap of DP dissociation. After dissociation, the hybridized probes were magnetically separated by a streptavidin-biotin complex. Especially, the ability to establish such a hairpin-type DP provided a powerful tool that could be used to hide the cut sequence (CS) and avoid false-positive signals. The cleaved CS initiated the CHA reaction and allowed superior fluorescence signal generation. Owing to the high specificity of FEN 1 for single base recognition, only the MT could be distinguished from the wild-type target and mismatched DNA. Owing to the dual signal amplification, as low as 0.36 fM MT and 1% mutation abundance from the mixtures could be detected, respectively. Furthermore, it could accurately identify SNPs from human cancer cells, as well as soybean leaf genome extracts. This strategy paves the way for the development of more precise and sensitive tools for diagnosing early onset diseases as well as molecular design breeding tools.

Dual-Energy CT Deep Learning Radiomics to Predict Macrotrabecular-Massive Hepatocellular Carcinoma.

Background It is unknown whether the additional information provided by multiparametric dual-energy CT (DECT) could improve the noninvasive diagnosis of the aggressive macrotrabecular-massive (MTM) subtype of hepatocellular carcinoma (HCC). Purpose To evaluate the diagnostic performance of dual-phase contrast-enhanced multiparametric DECT for predicting MTM HCC. Materials and Methods Patients with histopathologic examination-confirmed HCC who underwent contrast-enhanced DECT between June 2019 and June 2022 were retrospectively recruited from three independent centers (center 1, training and internal test data set; centers 2 and 3, external test data set). Radiologic features were visually analyzed and combined with clinical information to establish a clinical-radiologic model. Deep learning (DL) radiomics models were based on DL features and handcrafted features extracted from virtual monoenergetic images and material composition images on dual phase using binary least absolute shrinkage and selection operators. A DL radiomics nomogram was developed using multivariable logistic regression analysis. Model performance was evaluated with the area under the receiver operating characteristic curve (AUC), and the log-rank test was used to analyze recurrence-free survival. Results A total of 262 patients were included (mean age, 54 years ± 12 [SD]; 225 men [86%]; training data set, n = 146 [56%]; internal test data set, n = 35 [13%]; external test data set, n = 81 [31%]). The DL radiomics nomogram better predicted MTM than the clinical-radiologic model (AUC = 0.91 vs 0.77, respectively, for the training set [P < .001], 0.87 vs 0.72 for the internal test data set [P = .04], and 0.89 vs 0.79 for the external test data set [P = .02]), with similar sensitivity (80% vs 87%, respectively; P = .63) and higher specificity (90% vs 63%; P < .001) in the external test data set. The predicted positive MTM groups based on the DL radiomics nomogram had shorter recurrence-free survival than predicted negative MTM groups in all three data sets (training data set, P = .04; internal test data set, P = .01; and external test data set, P = .03). Conclusion A DL radiomics nomogram derived from multiparametric DECT accurately predicted the MTM subtype in patients with HCC. © RSNA, 2023 Supplemental material is available for this article. See also the editorial by Chu and Fishman in this issue.

Laser Induced Coffee-Ring Structure through Solid-Liquid Transition for Color Printing.

Metallic micro/nano structures with special physicochemical properties have undergone rapid development owing to their broad applications in micromachines and microdevices. Ultrafast laser processing is generally accepted as an effective technology for functional structures manufacture, however, the controllable fabrication of specific metallic micro/nano structures remains a challenge. Here, this work proposes a novel strategy of laser induced transient solid-liquid transition to fabricate unique structures. Through modulating the transient state of metal from solid to liquid phase using the initial pulse excitation, the subsequent ultrafast pulse-induced recoil pressure can suppress the plasma emission and removal of liquid phase metals, resulting in the controllable fabrication of coffee-ring structures. The solid-liquid transition dynamics, which related with the transient reflectivity and plasma intensity, are revealed by established two temperature model coupled with molecular dynamics model. The coffee-ring structure exhibits tunable structure color owing to various optical response, which can be used for color printing with large scale and high resolution. This work provides a promising strategy for fabricating functional micro/nano structures, which can greatly broaden the potential applications.

The role of computed tomography features in assessing response to neoadjuvant chemotherapy in locally advanced gastric cancer.

OBJECTIVE: To compare the computed tomography (CT) images of patients with locally advanced gastric cancer (GC) before and after neoadjuvant chemotherapy (NAC) in order to identify CT features that could predict pathological response to NAC. METHODS: We included patients with locally advanced GC who underwent gastrectomy after NAC from September 2016 to September 2021. We retrieved and collected the patients' clinicopathological characteristics and CT images before and after NAC. We analyzed CT features that could differentiate responders from non-responders and established a logistic regression equation based on these features. RESULTS: We included 97 patients (69 [71.1%] men; median [range] age, 60 [26-75] years) in this study, including 66 (68.0%) responders and 31 (32.0%) non-responders. No clinicopathological variable prior to treatment was significantly associated with pathological response. Out of 16 features, three features (ratio of tumor thickness reduction, ratio of reduction of primary tumor attenuation in arterial phase, and ratio of reduction of largest lymph node attenuation in venous phase) on logistic regression analysis were used to establish a regression equation that demonstrated good discrimination performance in predicting pathological response (area under receiver operating characteristic curve 0.955; 95% CI, 0.911-0.998). CONCLUSION: Logistic regression equation based on three CT features can help predict the pathological response of patients with locally advanced GC to NAC.

Preoperative diagnosis of metastatic lymph nodes by CT-histopathologic matching analysis in gastric adenocarcinoma using dual-layer spectral detector CT.

OBJECTIVES: There still remain challenges to accurate diagnosis of lymph node (LN) involvement in gastric cancer (GC) on conventional CT. This study evaluated the quantitative data derived from dual-layer spectral detector CT (DLCT) for preoperative diagnosis of metastatic LNs compared to conventional CT images. METHODS: Patients with adenocarcinoma scheduled for gastrectomy were enrolled in this prospective study from July, 2021, to February, 2022. Regional LNs were labeled on preoperative DLCT. The LNs were located and matched using carbon nanoparticle solution during surgery according to their locations and anatomic landmarks on preoperative images. The matched LNs were randomly split into training and validation cohorts in a ratio of 2:1. The DLCT quantitative parameters in the training cohort were investigated using logistic regression models to identify independent predictors of metastatic LNs, and these predictors were subsequently applied to the validation cohort. Receiver operating characteristic curves were compared between the DLCT parameters and conventional CT images. RESULTS: Fifty-five patients were included in the study, with 267 successfully matched LNs (90 metastatic, 177 nonmetastatic). Independent predictors included arterial phase CT attenuation on 70-keV images, venous phase electron density, and clustered feature. These combination predictors had areas under the curve (AUC) of 0.855 and 0.907 in the training and validation cohorts, respectively. Compared to conventional CT criteria alone, the model had higher AUC and accuracy (0.741 vs. 0.907, 75.28% vs. 87.64%; p < 0.01) for LN diagnosis. CONCLUSION: Incorporating DLCT parameters improved preoperative diagnosis of LN metastasis in GC, increasing the accuracy of clinical N stage. CLINICAL RELEVANCE STATEMENT: Compared to conventional CT criteria, quantitative parameters from dual-layer spectral detector CT showed higher diagnostic efficacy for the preoperative diagnosis of lymph node metastases in gastric cancer, increasing the accuracy of clinical N stage. KEY POINTS: • Quantitative parameters from dual-layer spectral detector CT are useful for the preoperative diagnosis of lymph node metastases in gastric adenocarcinoma, increasing the accuracy of clinical N stage. • The values for metastatic lymph nodes are higher than those of nonmetastatic ones. The arterial phase of CT attenuation on 70-keV images, venous phase of electron density, and clustered feature independently predicted lymph node metastases. • Prediction model had area under the curve of 0.907, sensitivity of 81.82%, specificity of 91.07%, and accuracy of 87.64% for the preoperative diagnosis of lymph node metastasis.

Simultaneous Measurement of Single-Cell Mechanics and Cell-to-Materials Adhesion Using Fluidic Force Microscopy.

The connection between cells and their substrate is essential for biological processes such as cell migration. Atomic force microscopy nanoindentation has often been adopted to measure single-cell mechanics. Very recently, fluidic force microscopy has been developed to enable rapid measurements of cell adhesion. However, simultaneous characterization of the cell-to-material adhesion and viscoelastic properties of the same cell is challenging. In this study, we present a new approach to simultaneously determine these properties for single cells, using fluidic force microscopy. For MCF-7 cells grown on tissue-culture-treated polystyrene surfaces, we found that the adhesive force and adhesion energy were correlated for each cell. Well-spread cells tended to have stronger adhesion, which may be due to the greater area of the contact between cellular adhesion receptors and the surface. By contrast, the viscoelastic properties of MCF-7 cells cultured on the same surface appeared to have little dependence on cell shape. This methodology provides an integrated approach to better understand the biophysics of multiple cell types.

The Potential Role of FREM1 and Its Isoform TILRR in HIV-1 Acquisition through Mediating Inflammation.

FREM1 (Fras-related extracellular matrix 1) and its splice variant TILRR (Toll-like interleukin-1 receptor regulator) have been identified as integral components of innate immune systems. The potential involvement of FREM1 in HIV-1 (human immunodeficiency virus 1) acquisition was suggested by a genome-wide SNP (single nucleotide polymorphism) analysis of HIV-1 resistant and susceptible sex workers enrolled in the Pumwani sex worker cohort (PSWC) in Nairobi, Kenya. The studies showed that the minor allele of a FREM1 SNP rs1552896 is highly enriched in the HIV-1 resistant female sex workers. Subsequent studies showed that FREM1 mRNA is highly expressed in tissues relevant to mucosal HIV-1 infection, including cervical epithelial tissues, and TILRR is a major modulator of many genes in the NF-κB signal transduction pathway. In this article, we review the role of FREM1 and TILRR in modulating inflammatory responses and inflammation, and how their influence on inflammatory responses of cervicovaginal tissue could enhance the risk of vaginal HIV-1 acquisition.

pH-Responsive Oxygen Nanobubbles for Spontaneous Oxygen Delivery in Hypoxic Tumors.

Tumor hypoxia is a significant factor leading to the resistance of tumors to treatment, especially for photodynamic therapy and radiotherapy where oxygen is needed to kill cancer cells. Oxygen delivery agents such as oxygen-saturated perfluorocarbon nanoemulsions and lipid oxygen microbubbles have been employed to supply oxygen to hypoxic tumors with ultrasound activation. Such oxygen delivery systems are still associated with several drawbacks, including premature oxygen release and the dependence of external stimuli. To address these limitations, we developed oxygen nanobubbles that were enclosed by the acetalated dextran polymer shells for spontaneous oxygeneration in response to a minor pH drop in the tumor microenvironment. The acetalated dextran polymer shell serves as a robust barrier against gas dissolution in the circulating blood to retain the majority of the oxygen payload, and its pH-responsive property enables an abrupt burst release of oxygen in the mild acidic tumor microenvironment. The acetalated dextran oxygen nanobubbles exhibited excellent stability and biocompatibility. In vitro and in vivo experiments were conducted to investigate the pH-responsive oxygen release. The external stimuli-free supply of oxygen by the acetalated dextran oxygen nanobubbles was evaluated on CNE2 tumor-bearing mice, and the intratumoral oxygen level increased by 6-fold after the administration of the oxygen nanobubbles, manifesting that our pH-responsive oxygen nanobubbles hold great potential as a potent oxygen delivery agent to overcome the hypoxia-induced resistance.

Kinetics of Serological Responses in Critically Ill Patients Hospitalized With 2009 Pandemic Influenza A(H1N1) Virus Infection in Canada, 2009-2011.

Background: The kinetics of the antibody response during severe influenza are not well documented. Methods: Critically ill patients infected with 2009 pandemic influenza A(H1N1) virus (A[H1N1]pdm09), confirmed by reverse-transcription polymerase chain reaction analysis or seroconversion (defined as a ≥4-fold rise in titers), during 2009-2011 in Canada were prospectively studied. Antibody titers in serially collected sera were determined using hemagglutinin inhibition (HAI) and microneutralization assays. Average antibody curves were estimated using linear mixed-effects models and compared by patient outcome, age, and corticosteroid treatment. Results: Of 47 patients with A(H1N1)pdm09 virus infection (median age, 47 years), 59% had baseline HAI titers of <40, and 68% had baseline neutralizing titers of <40. Antibody titers rose quickly after symptom onset, and, by day 14, 83% of patients had HAI titers of ≥40, and 80% had neutralizing titers ≥40. Baseline HAI titers were significantly higher in patients who died compared with patients who survived; however, the antibody kinetics were similar by patient outcome and corticosteroid treatment. Geometric mean titers over time in older patients were lower than those in younger patients. Conclusions: Critically ill patients with influenza A(H1N1)pdm09 virus infection had strong HAI and neutralizing antibody responses during their illness. Antibody kinetics differed by age but were not associated with patient outcome.

Polymorphisms of large effect explain the majority of the host genetic contribution to variation of HIV-1 virus load.

Previous genome-wide association studies (GWAS) of HIV-1-infected populations have been underpowered to detect common variants with moderate impact on disease outcome and have not assessed the phenotypic variance explained by genome-wide additive effects. By combining the majority of available genome-wide genotyping data in HIV-infected populations, we tested for association between ∼8 million variants and viral load (HIV RNA copies per milliliter of plasma) in 6,315 individuals of European ancestry. The strongest signal of association was observed in the HLA class I region that was fully explained by independent effects mapping to five variable amino acid positions in the peptide binding grooves of the HLA-B and HLA-A proteins. We observed a second genome-wide significant association signal in the chemokine (C-C motif) receptor (CCR) gene cluster on chromosome 3. Conditional analysis showed that this signal could not be fully attributed to the known protective CCR5Δ32 allele and the risk P1 haplotype, suggesting further causal variants in this region. Heritability analysis demonstrated that common human genetic variation-mostly in the HLA and CCR5 regions-explains 25% of the variability in viral load. This study suggests that analyses in non-European populations and of variant classes not assessed by GWAS should be priorities for the field going forward.

Mauritian cynomolgus macaques with M3M4 MHC genotype control SIVmac251 infection.

BACKGROUND: Understanding natural HIV control may lead to new preventative or therapeutic strategies. Several protective major histocompatibility complex (MHC) genotypes were found in humans and rhesus macaques. Here, we report a simian immunodeficiency virus (SIV) controller MHC genotype in Mauritian cynomolgus macaques (MCMs). METHODS: Twelve MHC-genotyped MCMs were infected with SIVmac251 and monitored for viral loads and CD4+ T-cell counts. RESULTS: Two macaques with M3M4 genotype exhibited the lowest peak viral loads (log plasma SIV RNA copies/mL), nearly 3 logs lower than those in most macaques with other MHC haplotype combinations, and set point viral loads below the level of detection limit by RT-qPCR (<2 log RNA copies/mL). They maintained healthy CD4+ T-cell counts of >500 cells/µL blood, while CD4 counts in the vast majority of other macaques were below this level. CONCLUSIONS: The M3M4 MHC genotype may confer enhanced control of SIV replication in MCMs.

A novel HIV vaccine targeting the protease cleavage sites.

HIV preferentially infects activated CD4+ T cells and mutates rapidly. The classical vaccine approach aimed to generate broad immune responses to full HIV proteins largely failed to address the potential adverse impact of increased number of activated CD4+ T cells as viral targets. Learning from natural immunity observed in a group of HIV resistant Kenyan female sex workers, we are testing a novel vaccine approach. It focuses immune response to the highly conserved sequences surrounding the HIV protease cleavage sites (PCS) to disrupt viral maturation, while limiting excessive immune activation. Our pilot studies using nonhuman primate SIV infection models suggest that this approach is feasible and promising.

Risk for ACPA-positive rheumatoid arthritis is driven by shared HLA amino acid polymorphisms in Asian and European populations.

Previous studies have emphasized ethnically heterogeneous human leukocyte antigen (HLA) classical allele associations to rheumatoid arthritis (RA) risk. We fine-mapped RA risk alleles within the major histocompatibility complex (MHC) in 2782 seropositive RA cases and 4315 controls of Asian descent. We applied imputation to determine genotypes for eight class I and II HLA genes to Asian populations for the first time using a newly constructed pan-Asian reference panel. First, we empirically measured high imputation accuracy in Asian samples. Then we observed the most significant association in HLA-DRß1 at amino acid position 13, located outside the classical shared epitope (Pomnibus = 6.9 × 10(-135)). The individual residues at position 13 have relative effects that are consistent with published effects in European populations (His > Phe > Arg > Tyr ≅ Gly > Ser)--but the observed effects in Asians are generally smaller. Applying stepwise conditional analysis, we identified additional independent associations at positions 57 (conditional Pomnibus = 2.2 × 10(-33)) and 74 (conditional Pomnibus = 1.1 × 10(-8)). Outside of HLA-DRß1, we observed independent effects for amino acid polymorphisms within HLA-B (Asp9, conditional P = 3.8 × 10(-6)) and HLA-DPß1 (Phe9, conditional P = 3.0 × 10(-5)) concordant with European populations. Our trans-ethnic HLA fine-mapping study reveals that (i) a common set of amino acid residues confer shared effects in European and Asian populations and (ii) these same effects can explain ethnically heterogeneous classical allelic associations (e.g. HLA-DRB1*09:01) due to allele frequency differences between populations. Our study illustrates the value of high-resolution imputation for fine-mapping causal variants in the MHC.

Predicting HLA alleles from high-resolution SNP data in three Southeast Asian populations.

The major histocompatibility complex (MHC) containing the classical human leukocyte antigen (HLA) Class I and Class II genes is among the most polymorphic and diverse regions in the human genome. Despite the clinical importance of identifying the HLA types, very few databases jointly characterize densely genotyped single nucleotide polymorphisms (SNPs) and HLA alleles in the same samples. To date, the HapMap presents the only public resource that provides a SNP reference panel for predicting HLA alleles, constructed with four collections of individuals of north-western European, northern Han Chinese, cosmopolitan Japanese and Yoruba Nigerian ancestry. Owing to complex patterns of linkage disequilibrium in this region, it is unclear whether the HapMap reference panels can be appropriately utilized for other populations. Here, we describe a public resource for the Singapore Genome Variation Project with: (i) dense genotyping across ∼ 9000 SNPs in the MHC; (ii) four-digit HLA typing for eight Class I and Class II loci, in 96 southern Han Chinese, 89 Southeast Asian Malays and 83 Tamil Indians. This resource provides population estimates of the frequencies of HLA alleles at these eight loci in the three population groups, particularly for HLA-DPA1 and HLA-DPB1 that were not assayed in HapMap. Comparing between population-specific reference panels and a cosmopolitan panel created from all four HapMap populations, we demonstrate that more accurate imputation is obtained with population-specific panels than with the cosmopolitan panel, especially for the Malays and Indians but even when imputing between northern and southern Han Chinese. As with SNP imputation, common HLA alleles were imputed with greater accuracy than low-frequency variants.

Association study of common genetic variants and HIV-1 acquisition in 6,300 infected cases and 7,200 controls.

Multiple genome-wide association studies (GWAS) have been performed in HIV-1 infected individuals, identifying common genetic influences on viral control and disease course. Similarly, common genetic correlates of acquisition of HIV-1 after exposure have been interrogated using GWAS, although in generally small samples. Under the auspices of the International Collaboration for the Genomics of HIV, we have combined the genome-wide single nucleotide polymorphism (SNP) data collected by 25 cohorts, studies, or institutions on HIV-1 infected individuals and compared them to carefully matched population-level data sets (a list of all collaborators appears in Note S1 in Text S1). After imputation using the 1,000 Genomes Project reference panel, we tested approximately 8 million common DNA variants (SNPs and indels) for association with HIV-1 acquisition in 6,334 infected patients and 7,247 population samples of European ancestry. Initial association testing identified the SNP rs4418214, the C allele of which is known to tag the HLA-B*57:01 and B*27:05 alleles, as genome-wide significant (p = 3.6 × 10⁻¹¹). However, restricting analysis to individuals with a known date of seroconversion suggested that this association was due to the frailty bias in studies of lethal diseases. Further analyses including testing recessive genetic models, testing for bulk effects of non-genome-wide significant variants, stratifying by sexual or parenteral transmission risk and testing previously reported associations showed no evidence for genetic influence on HIV-1 acquisition (with the exception of CCR5Δ32 homozygosity). Thus, these data suggest that genetic influences on HIV acquisition are either rare or have smaller effects than can be detected by this sample size.

Enhanced plasmonic light absorption engineering of graphene: simulation by boundary-integral spectral element method.

Graphene's relatively poor absorption is an essential obstacle for designing graphene-based photonic devices with satisfying photo-responsivity. To enhance the tunable light absorption of graphene, appropriate excitation of localized surface plasmon resonance is considered as a promising approach. In this work, the strategy of incorporating periodic cuboid gold nanoparticle (NP) cluster arrays and cylindrical gold NP arrays with Bragg reflectors into graphene-based photodetectors are theoretically studied by the boundary-integral spectral element method (BI-SEM). With the BI-SEM, the models can be numerically analyzed with excellent accuracy and efficiency. Numerical simulation shows that the proposed structures can effectively engineer the light absorption in graphene by tuning plasmon resonance. In the spectra of 300 nm to 1000 nm, a maximum light absorption of 67.54% is observed for the graphene layer with optimal parameters of the photodetector model.

Boundary integral spectral element method analyses of extreme ultraviolet multilayer defects.

Extreme ultraviolet (EUV) lithography is an emerging technology for high-density semiconductor patterning. Multilayer distortion caused by mask defects is regarded as one of the critical challenges of EUV lithography. To simulate the influence of the defected nanoscale structures with high accuracy and efficiency, we have developed a boundary integral spectral element method (BI-SEM) that combines the SEM with a set of surface integral equations. The SEM is used to solve the interior computational domain, while the open boundaries are truncated by the surface integral equations. Both two-dimensional (2D) and three-dimensional (3D) EUV cases are simulated. Through comparing the performance of this method with the conventional finite element method (FEM), it is shown that the proposed BI-SEM can greatly decrease both the memory cost and the computation time. For typical 2D problems, we show that the BI-SEM is 11 and 1.25 times more efficient than the FEM in terms of memory and CPU time, respectively, while for 3D problems, these factors are over 14 and 2, respectively, for smaller problems; realistic 3D problems that cannot be solved by the conventional FEM can be accurately simulated by the BI-SEM.