Two-Step Machine Learning Approach for Charge-Transfer Coupling with Structurally Diverse Data.

Electronic coupling is important in determining charge-transfer rates and dynamics. Coupling strength is sensitive to both intermolecular, e.g., orientation or distance, and intramolecular degrees of freedom. Hence, it is challenging to build an accurate machine learning model to predict electronic coupling of molecular pairs, especially for those derived from the amorphous phase, for which intermolecular configurations are much more diverse than those derived from crystals. In this work, we devise a new prediction algorithm that employs two consecutive KRR models. The first model predicts molecular orbitals (MOs) from structural variation for each fragment, and coupling is further predicted by using the overlap integral included in a second model. With our two-step procedure, we achieved mean absolute errors of 0.27 meV for an ethylene dimer and 1.99 meV for a naphthalene pair, much improved accuracy amounting to 14-fold and 3-fold error reductions, respectively. In addition, MOs from the first model can also be the starting point to obtain other quantum chemical properties from atomistic structures. This approach is also compatible with a MO predictor with sufficient accuracy.

CXCL13 variant predicts pegylated-interferon α treatment response in HBeAg-positive chronic hepatitis B patients.

As a key immune cytokine, C-X-C motif chemokine ligand 13 (CXCL13) has been reported to play critical roles in immune control of hepatitis B virus (HBV) infection. We aimed to screen single-nucleotide polymorphisms (SNPs) of CXCL13 for predicting response to pegylated interferon-alpha (PegIFNα) therapy of chronic hepatitis B (CHB) patients. Two independent cohorts with a total of 945 (Cohort 1, n = 238; Cohort 2, n = 707) hepatitis B e antigen (HBeAg)-positive CHB patients treated with PegIFNα were enrolled in this retrospective cohort study. Eight candidate SNPs were selected through gene-wide SNP mining within or flanking CXCL13. A polygenic score (PGS) was utilized to assess the cumulative effects of multiple SNPs. The associations of candidate SNPs and PGS with combined response (CR, defined as the combination of HBeAg seroconversion and HBV DNA level <3.3log10 IU/mL) and hepatitis B surface antigen (HBsAg) level were evaluated. Among the eight candidate SNPs, rs76084459 which is located at upstream of CXCL13 was significantly associated with both CR (p = 0.002) and HBsAg level (p = 0.015). A PGS integrating CXCL13_rs76084459 and five other SNPs, which were previously identified as predictors of PegIFNα treatment response, was further strongly correlated with CR (p = 1.759 × 10-10 ) and HBsAg level (p = 0.004). This study demonstrated that CXCL13_rs76084459 can predict response to PegIFNα treatment of HBeAg-positive CHB patients. A PGS composed of six SNPs including CXCL13_rs76084459 predicts PegIFNα treatment response better.

Machine-learned dynamic disorder of electron transfer coupling.

Electron transfer (ET) is a fundamental process in chemistry and biochemistry, and electronic coupling is an important determinant of the rate of ET. However, the electronic coupling is sensitive to many nuclear degrees of freedom, particularly those involved in intermolecular movements, making its characterization challenging. As a result, dynamic disorder in electron transfer coupling has rarely been investigated, hindering our understanding of charge transport dynamics in complex chemical and biological systems. In this work, we employed molecular dynamic simulations and machine-learning models to study dynamic disorder in the coupling of hole transfer between neighboring ethylene and naphthalene dimer. Our results reveal that low-frequency modes dominate these dynamics, resulting primarily from intermolecular movements such as rotation and translation. Interestingly, we observed an increasing contribution of translational motion as temperature increased. Moreover, we found that coupling is sub-Ohmic in its spectral density character, with cut-off frequencies in the range of 102 cm-1. Machine-learning models allow direct study of dynamics of electronic coupling in charge transport with sufficient ensemble trajectories, providing further new insights into charge transporting dynamics.

The effects of the interactions of STAT4 rs7574865 with HBV mutations on the risk of hepatocellular carcinoma.

Signal transducer and activator of transcription 4 (STAT4) is closely related to liver diseases and affects the processes of inflammation and carcinogenesis by regulating immune responses. A single-nucleotide polymorphism rs7574865 (T > G) in STAT4 has been reported to be associated with the risk of hepatocellular carcinoma (HCC). In addition, hepatitis B virus (HBV) mutations are crucial risk factors for HBV-induced HCC. However, the effects of the interactions of STAT4 rs7574865 with HBV mutations on the risk of HCC remain unknown. Rs7574865 was genotyped in 846 healthy controls (HCs), 968 chronic hepatitis B (CHB) subjects, 316 liver cirrhosis (LC) subjects and 1021 HCC subjects using Sequenom MassArray. HBV mutations were detected via direct sequencing. Multivariate logistic regression analysis was used to evaluate the effects of the interactions of STAT4 rs7574865 with HBV mutations on the risk of HCC. We found that the rs7574865 TT genotype was significantly associated with HBeAg seroconversion (TT vs. GG, p = 0.012; TT vs. GT, p = 0.033). The rs7574865 GG genotype was significantly associated with increased risks of CHB (p = 0.048), LC (p = 0.005) and HCC (p < 0.001). The interaction term between rs7574865 and HBV C1913A significantly increased the risk of progression from CHB to HCC (p = 0.038), while the interaction term between rs7574865 and HBV T1674C significantly increased the risk of progression from LC to HCC (p = 0.023). STAT4 rs7574865 is significantly associated with the risks of CHB, LC and HCC. The interactions of rs7574865 with HBV C1913A and T1674C mutations significantly increase the risk of HCC, which have the potential to identify HBV-infected individuals who tend to progress from CHB or LC to HCC.

Molecular and nano structures of chiral PEDOT derivatives influence the enantiorecognition of biomolecules. In silico analysis of chiral recognition.

In this study we investigated the synergistic effects of the chirality (molecular structure) and surface morphology (nanostructure) of a newly designed sensing platform for the stereoselective recognition of biomolecules. We synthesized 3,4-ethylenedioxythiophene monomers presenting an OH functional group on the side chain (EDOT-OH) with either R or S chirality and then electropolymerized them in a template-free manner to engineer poly(EDOT-OH) nanotubes and smooth films with R or S chirality. We used a quartz crystal microbalance (QCM) to examine the differential binding of fetal bovine serum, RGD peptide, insulin, and (R)- and (S)-mandelic acid (MA) on these chiral polymeric platforms. All of these biomolecules bound stereoselectively and with greater affinity toward the nanotubes than to the smooth films. The sensitive chiral recognition of (S)- and (R)-MA on the (R)-poly(EDOT-OH) nanotube surface occurred with the highest chiral discrepancy ratio of 1.80. In vitro experiments revealed a greater degree of protein deposition from MCF-7 cells on the chiral nanotube surfaces. We employed ab initio molecular dynamics simulations and density functional theory calculations to investigate the mechanism underlying the sensitive chiral recognition between the chiral sensing platforms and the chiral analyte molecules.

Knowledge-based analyses reveal new candidate genes associated with risk of hepatitis B virus related hepatocellular carcinoma.

BACKGROUND: Recent genome-wide association studies (GWASs) have suggested several susceptibility loci of hepatitis B virus (HBV)-related hepatocellular carcinoma (HCC) by statistical analysis at individual single-nucleotide polymorphisms (SNPs). However, these loci only explain a small fraction of HBV-related HCC heritability. In the present study, we aimed to identify additional susceptibility loci of HBV-related HCC using advanced knowledge-based analysis. METHODS: We performed knowledge-based analysis (including gene- and gene-set-based association tests) on variant-level association p-values from two existing GWASs of HBV-related HCC. Five different types of gene-sets were collected for the association analysis. A number of SNPs within the gene prioritized by the knowledge-based association tests were selected to replicate genetic associations in an independent sample of 965 cases and 923 controls. RESULTS: The gene-based association analysis detected four genes significantly or suggestively associated with HBV-related HCC risk: SLC39A8, GOLGA8M, SMIM31, and WHAMMP2. The gene-set-based association analysis prioritized two promising gene sets for HCC, cell cycle G1/S transition and NOTCH1 intracellular domain regulates transcription. Within the gene sets, three promising candidate genes (CDC45, NCOR1 and KAT2A) were further prioritized for HCC. Among genes of liver-specific expression, multiple genes previously implicated in HCC were also highlighted. However, probably due to small sample size, none of the genes prioritized by the knowledge-based association analyses were successfully replicated by variant-level association test in the independent sample. CONCLUSIONS: This comprehensive knowledge-based association mining study suggested several promising genes and gene-sets associated with HBV-related HCC risks, which would facilitate follow-up functional studies on the pathogenic mechanism of HCC.

Experimental and theoretical rationalization for the base pairing abilities of inosine, guanosine, adenosine, and their corresponding 8-oxo-7,8-dihydropurine, and 8-bromopurine analogues within A-form duplexes of RNA.

Inosine is an important RNA modification, furthermore RNA oxidation has gained interest due, in part, to its potential role in the development/progression of disease as well as on its impact on RNA structure and function. In this report we established the base pairing abilities of purine nucleobases G, I, A, as well as their corresponding, 8-oxo-7,8-dihydropurine (common products of oxidation at the C8-position of purines), and 8-bromopurine (as probes to explore conformational changes), derivatives, namely 8-oxoG, 8-oxoI, 8-oxoA, 8-BrG, and 8-BrI. Dodecamers of RNA were obtained using standard phosphoramidite chemistry via solid-phase synthesis, and used as models to establish the impact that each of these nucleobases have on the thermal stability of duplexes, when base pairing to canonical and noncanonical nucleobases. Thermal stabilities were obtained from thermal denaturation transition (Tm ) measurements, via circular dichroism (CD). The results were then rationalized using models of base pairs between two monomers, via density functional theory (DFT), that allowed us to better understand potential contributions from H-bonding patterns arising from distinct conformations. Overall, some of the important results indicate that: (a) an anti-I:syn-A base pair provides thermal stability, due to the absence of the exocyclic amine; (b) 8-oxoG base pairs like U, and does not induce destabilization within the duplex when compared to the pyrimidine ring; (c) a U:G wobble-pair is only stabilized by G; and (d) 8-oxoA displays an inherited base pairing promiscuity in this sequence context. Gaining a better understanding of how this oxidatively generated lesions potentially base pair with other nucleobases will be useful to predict various biological outcomes, as well as in the design of biomaterials and/or nucleotide derivatives with biological potential.

Heat Transport in a Spin-Boson Model at Low Temperatures: A Multilayer Multiconfiguration Time-Dependent Hartree Study.

Extending our previous work, quantum dynamic simulations are performed to study low temperature heat transport in a spin-boson model where a two-level subsystem is coupled to two independent harmonic baths. Multilayer multiconfiguration time-dependent Hartree theory is used to numerically evaluate the thermal flux, for which the bath is represented by hundreds to thousands of modes. The simulation results are compared with the approximate Redfield theory approach, and the physics is analyzed versus different physical parameters.

Photocycloaddition of S,S-Dioxo-benzothiophene-2-methanol, Reactivity in the Solid State and in Solution: Mechanistic Studies and Diastereoselective Formation of Cyclobutyl Rings.

The formation of cyclobutane rings is a promising strategy in the development of potential drugs and/or synthetic intermediates, typically challenging to obtain due to their constrained nature. In this work, the [2 + 2] photocycloaddition reaction of S,S-dioxobenzothiophene-2-methanol was explored in microcrystalline powders and its outcome was compared to that observed in solution. It was found that the molecular constraints inherited within the crystal lattice provide an optimal environment that leads to photodimer 4 as the major product in ca. 9.6:0.4 diastereomeric ratios with conversions >95%. The photoreaction was analyzed via X-ray, displaying a crystalline-to-amorphous transformation and showing that units of monomer 2 align to generate the corresponding dimer with a syn-head-to-tail regio- and diastereoselectivity. This result contrasted with that obtained in solution, where the diastereomeric ratio varied as a function of the excited state that is generated, to yield mixtures of dimers 4 and 5 (anti-head-to-tail), or exclusively 5 in the triplet-sensitized photoreaction, in the presence of benzophenone. Density functional theory was used to elucidate a plausible detailed mechanism for the phototransformation, which aided in justifying the results that led to the corresponding dimers. X-ray crystallography allowed us to establish the stereochemical assignment of the obtained cyclobutyl rings. Thus, the use of solid-state or solution photochemistry can be used to gain control of diastereo- and regioselectivities in the formation of this important moiety.

Approximate DFT-based methods for generating diabatic states and calculating electronic couplings: models of two and more states.

Four types of density functional theory (DFT)-based approaches are assessed in this work for the approximate construction of diabatic states and the evaluation of electronic couplings between these states. These approaches include the constrained DFT (CDFT) method, the constrained noninteracting electron (CNE) model to post-process Kohn-Sham operators, the approximate block-diagonalization (BD) of the Kohn-Sham operators, and the generalized Mulliken-Hush method. It is shown that the first three approaches provide a good description for long-distance intermolecular electron transfer (ET) reactions. On the other hand, inconsistent results were found when applying these approaches to intramolecular ET in strongly coupled, mixed-valence systems. Model analysis shows that this discrepancy is caused by the inappropriate use of the two-state model rather than the defects of the approaches themselves. The situation is much improved when more states are included in the model electronic Hamiltonian. The CNE and BD approaches can thus serve as efficient and robust alternatives for building ET models based on DFT calculations.

Direct Aryloxylation/Alkyloxylation of Dialkyl Phosphonates for the Synthesis of Mixed Phosphonates.

A strategy for the direct functionalization strategy of inertial dialkyl phosphonates with hydroxy compounds to afford diverse mixed phosphonates with good yields and functional-group tolerance has been developed. Mechanistic investigations involving both NMR studies and DFT studies suggest that an unprecedented highly reactive PV species (phosphoryl pyridin-1-ium salt), a key intermediate for this new synthetic transformation, is generated in situ from dialkyl phosphonate in the presence of Tf2 O/pyridine.

Dynamic and specific immune responses against multiple tumor antigens were elicited in patients with hepatocellular carcinoma after cell-based immunotherapy.

BACKGROUND: Hepatocellular carcinoma (HCC) is one of the most common cancers in China and frequently occurs with chronic hepatitis B virus infection. To investigate whether cell-based cancer immunotherapy induces tumor specific immune responses in patients with HCC and provides clinical benefits, as well as to elucidate the most immunogenic tumor associated antigens (TAAs), multiple antigen stimulating cellular therapy (MASCT) was applied in addition to standard of care. METHODS: Mature dendritic cells (DCs) and activated T cells prepared for MASCT were generated from autologous peripheral blood mononuclear cells (PBMCs). DCs were loaded with a peptide pool of multiple HCC-related tumor antigens, and T cells were stimulated by these DCs. RESULTS: Thirteen patients with HCC received repeated MASCT after tumor resection during which their immune responses were examined. After three courses of MASCT, the frequency of regulatory T cells in the patients' PBMCs significantly decreased (p < 0.001), while the antigen peptide pool-triggered T cell proliferation (p < 0.001) and IFNγ production (p = 0.001) were significantly enhanced. The specific T cell responses against each antigen in the pool were detected in 11 patients, but with individualized distinct patterns. The most immunogenic TAAs for HCC are survivin, CCND1, and RGS5. Moreover, the antigen-specific immune responses observed in tumor-free patients' PBMCs were significantly stronger than that in the patients with recurrence (p = 0.037). CONCLUSIONS: Our study demonstrates that MASCT is well-tolerated by patients with HCC and elicits strong and dynamic immune responses specifically against multiple tumor associated antigens, which may correlate with clinical outcomes.

Fate of heavy metals and evaluation of eutrophication in a wetland-reservoir system.

The fate of heavy metals (Cd, Cr, Cu, Ni, Pb, and Zn) in the water column, sediment, and macrophytic plants as well as a total phosphorus eutrophication model were evaluated by a field monitoring program in the LungLuanTan wetland-reservoir system in Taiwan. Zinc and Cd were found to have the highest and lowest partition coefficients, respectively. The levels of heavy metals in the sediment of the wetland were highest in the dry season. In fresh plant tissues and sediment, Cd had the highest bioconcentration factor during the study period. Furthermore, the results obtained using the total phosphorus model with time-variable volumes for reservoir eutrophication and observed values were in reasonable agreement. Based on the modeling results, appropriate watershed management strategies are proposed to restore the wetland-reservoir water quality.

Non-negligible Outer-Shell Reorganization Energy for Charge Transfer in Nonpolar Systems.

Many charge-transporting molecular systems function as ordered or disordered arrays of solid state materials composed of nonpolar (or weakly polar) molecules. Due to low dielectric constants for nonpolar systems, it is common to ignore the effects of outer-shell reorganization energy (λout). However, ignoring λout has not been properly supported and it can severely impact predictions and insights derived. Here, we estimate λout by two means: from experimental ultraviolet photoelectron spectra, in which vibronic progression in these spectra can be fitted with the widths of peaks determining the low-frequency component in reorganization energy, regarded to be closely associated with λout, and from molecular dynamic (MD) simulation of nonpolar molecules, in which disorder or fluctuation statistics for energies of charged molecules are calculated. An upper bound for λout was obtained as 505 and 549 meV for crystalline anthracene (140 K) and pentacene (50 K), respectively, by fitting of experimental data, and 212 and 170 meV, respectively, from MD simulations. These values are comparable to the inner-sphere reorganization energy (λin) arising from intramolecular vibration. With corresponding spectral density functions calculated, we found that λout is influenced both by low- and high-frequency dynamics, in which the former arises from constrained translational and rotational motions of surrounding molecules. In an amorphous state, about half of the λout's obtained are from high-frequency components, which is quite different from the conventional polar solvation. Moreover, crystalline systems exhibit super-Ohmic spectral density, whereas amorphous systems are sub-Ohmic.

A multi-state fragment charge difference approach for diabatic states in electron transfer: extension and automation.

The electron transfer (ET) rate prediction requires the electronic coupling values. The Generalized Mulliken-Hush (GMH) and Fragment Charge Difference (FCD) schemes have been useful approaches to calculate ET coupling from an excited state calculation. In their typical form, both methods use two eigenstates in forming the target charge-localized diabatic states. For problems involve three or four states, a direct generalization is possible, but it is necessary to pick and assign the locally excited or charge-transfer states involved. In this work, we generalize the 3-state scheme for a multi-state FCD without the need of manual pick or assignment for the states. In this scheme, the diabatic states are obtained separately in the charge-transfer or neutral excited subspaces, defined by their eigenvalues in the fragment charge-difference matrix. In each subspace, the Hamiltonians are diagonalized, and there exist off-diagonal Hamiltonian matrix elements between different subspaces, particularly the charge-transfer and neutral excited diabatic states. The ET coupling values are obtained as the corresponding off-diagonal Hamiltonian matrix elements. A similar multi-state GMH scheme can also be developed. We test the new multi-state schemes for the performance in systems that have been studied using more than two states with FCD or GMH. We found that the multi-state approach yields much better charge-localized states in these systems. We further test for the dependence on the number of state included in the calculation of ET couplings. The final coupling values are converged when the number of state included is increased. In one system where experimental value is available, the multi-state FCD coupling value agrees better with the previous experimental result. We found that the multi-state GMH and FCD are useful when the original two-state approach fails.

Enhancing Singlet Fission Coupling with Nonbonding Orbitals.

Singlet fission (SF) is a process where a singlet exciton is split into a pair of triplet excitons. The increase in the excitonic generation can be exploited to enhance the efficiency of solar cells. Molecules with conjugated π bonds are commonly developed for optoelectronic applications including SF, due to their low energy gaps. The electronic coupling for SF in such well-stacked π-conjugated molecule pairs can be rather limited due to the orthogonal π and π* orbital overlaps that are involved in the coupling elements, leading to a large cancellation in the coupling. In the present work, we show that such limits can be removed by involving triplet states of different origins, such as those with nonbonding n orbitals. We demonstrate such an effect for formaldehyde and methylenimine dimers, with a low-lying n-π* triplet state (T1) in addition to the π-π* triplet (T2). We show that the coupling can be enhanced by 40 times or more for the formaldehyde dimer, and 15 times or more for the methylenimine dimer, with the T1-T2 state as the end product of SF. With 1759 randomly oriented pairs of formaldehyde derived from a molecular dynamics simulation, the coupling from a singlet exciton to this T1-T2 state is, on an average, almost two times larger than that for a regular T1-T1 state. We investigated a few families that have been shown to be prospective candidates for SF, using our proposed strategy. However, our unfavorable results indicate that there are clear difficulties in fulfilling the ES1 ≳ ET1 + ET2 energy criterion. Nevertheless, our results provide a new molecular design concept for better SF (and triplet-triplet annihilation, TTA) materials that allows future development.

Identification of a Novel N7-Methylguanosine-Related LncRNA Signature Predicts the Prognosis of Hepatocellular Carcinoma and Experiment Verification.

(1) Background: It is well-known that long non-coding RNAs (lncRNAs) and N7-methylguanosine (m7G) contribute to hepatocellular carcinoma (HCC) progression. However, it remains unclear whether lncRNAs regulating m7G modification could predict HCC prognosis. Thus, we sought to explore the prognostic implications of m7G-related lncRNAs in HCC patients. (2) Methods: Prognostic M7G-related lncRNAs obtained from The Cancer Genome Atlas (TCGA) database were screened by co-expression analysis and univariate Cox regression analysis. Next, the m7G-related lncRNA signature (m7GRLSig) was conducted by Least absolute shrinkage and selection operator (LASSO) Cox regression and multivariate Cox regression analysis. Kaplan-Meier analysis and time-dependent receiver operating characteristics (ROC) assessed the prognostic abilities of our signature. Univariate and multivariate Cox regression, nomogram, and principal component analysis (PCA) were conducted to evaluate our signature. Subsequently, we investigated the role of m7GRLSig on the immune landscape and sensitivity to drugs in HCC patients. The potential function of lncRNAs obtained from the prognostic signature was explored by in vitro experiments. (3) Results: A novel m7GRLSig was identified using seven meaningful lncRNA (ZFPM2-AS1, AC092171.2, PIK3CD-AS2, NRAV, CASC19, HPN-AS1, AC022613.1). The m7GLPSig exhibited worse survival in the high-risk group and served as an independent prognostic factor. The m7GRLSig stratification was sensitive in assessing the immune landscape and sensitivity to drugs between the high-risk and low-risk groups. Finally, in vitro experiments confirmed that the knockdown of NRAV was accompanied by the downregulation of METTL1 during HCC progression. (4) Conclusions: The m7G-related signature is a potential predictor of HCC prognosis and contributes to individualize the effective drug treatment of HCC.

Human papillomavirus genotype attribution in invasive cervical cancer: a retrospective cross-sectional worldwide study.

BACKGROUND: Knowledge about the distribution of human papillomavirus (HPV) genotypes in invasive cervical cancer is crucial to guide the introduction of prophylactic vaccines. We aimed to provide novel and comprehensive data about the worldwide genotype distribution in patients with invasive cervical cancer. METHODS: Paraffin-embedded samples of histologically confirmed cases of invasive cervical cancer were collected from 38 countries in Europe, North America, central South America, Africa, Asia, and Oceania. Inclusion criteria were a pathological confirmation of a primary invasive cervical cancer of epithelial origin in the tissue sample selected for analysis of HPV DNA, and information about the year of diagnosis. HPV detection was done by use of PCR with SPF-10 broad-spectrum primers followed by DNA enzyme immunoassay and genotyping with a reverse hybridisation line probe assay. Sequence analysis was done to characterise HPV-positive samples with unknown HPV types. Data analyses included algorithms of multiple infections to estimate type-specific relative contributions. FINDINGS: 22,661 paraffin-embedded samples were obtained from 14,249 women. 10,575 cases of invasive cervical cancer were included in the study, and 8977 (85%) of these were positive for HPV DNA. The most common HPV types were 16, 18, 31, 33, 35, 45, 52, and 58 with a combined worldwide relative contribution of 8196 of 8977 (91%, 95% CI 90-92). HPV types 16 and 18 were detected in 6357 of 8977 of cases (71%, 70-72) of invasive cervical cancer. HPV types 16, 18, and 45 were detected in 443 of 470 cases (94%, 92-96) of cervical adenocarcinomas. Unknown HPV types that were identified with sequence analysis were 26, 30, 61, 67, 69, 82, and 91 in 103 (1%) of 8977 cases of invasive cervical cancer. Women with invasive cervical cancers related to HPV types 16, 18, or 45 presented at a younger mean age than did those with other HPV types (50·0 years [49·6-50·4], 48·2 years [47·3-49·2], 46·8 years [46·6-48·1], and 55·5 years [54·9-56·1], respectively). INTERPRETATION: To our knowledge, this study is the largest assessment of HPV genotypes to date. HPV types 16, 18, 31, 33, 35, 45, 52, and 58 should be given priority when the cross-protective effects of current vaccines are assessed, and for formulation of recommendations for the use of second-generation polyvalent HPV vaccines. Our results also suggest that type-specific high-risk HPV-DNA-based screening tests and protocols should focus on HPV types 16, 18, and 45.

Molecular Design of Ultrabright Semiconducting Polymer Dots with High NIR-II Fluorescence for 3D Tumor Mapping.

Fluorescence probes emitting in the second near-infrared (NIR-II, 1000-1700 nm) window with the ability for deep-tissue imaging in mammals herald a new era in surgical methodology. However, the brightness of these NIR-II probes is still far from satisfactory due to their low fluorescence quantum yields (QYs), preventing the observation of high-resolution images such as whole-organ vascular networks in real time. Described here is the molecular engineering of a series of semiconducting polymer dots (Pdots) incorporated with aggregation-induced emission moieties to exhibit the QYs as high as 14% in the NIR-II window. Benefiting from the ultrahigh brightness, a 1400 nm long-pass filter is utilized to realize in vivo 3D tumor mapping in mice. To further understand how the geometrical and electron structures of the semiconducting polymers affect their optical properties, the in-depth and thorough density-functional theory calculations are performed to interpret the experimental results. This study lays the groundwork for further molecular design of highly bright NIR-II Pdots.

STAT4: an immunoregulator contributing to diverse human diseases.

Signal transducer and activator of transcription 4 (STAT4) is a member of the STAT family and localizes to the cytoplasm. STAT4 is phosphorylated after a variety of cytokines bind to the membrane, and then dimerized STAT4 translocates to the nucleus to regulate gene expression. We reviewed the essential role played by STAT4 in a wide variety of cells and the pathogenesis of diverse human diseases, especially many kinds of autoimmune and inflammatory diseases, via activation by different cytokines through the Janus kinase (JAK)-STAT signaling pathway.