Direct Probe of Conical Intersection Photochemistry by Time-Resolved X-ray Magnetic Circular Dichroism.

The direct probing of photochemical dynamics by detecting the electronic coherence generated during passage through conical intersections is an intriguing challenge. The weak coherence signal and the difficulty in preparing purely excited wave packets that exclude coherence from other sources make it experimentally challenging. We propose to use time-resolved X-ray magnetic circular dichroism to probe the wave packet dynamics around the conical intersection. The magnetic field amplifies the relative strength of the electronic coherence signal compared to populations through the magnetic field response anisotropy. More importantly, since the excited state relaxation through conical intersections involves a change of parity, the magnetic coupling matches the symmetry of the response function with the electronic coherence, making the coherence signal only sensitive to the conical intersection induced coherence and excludes the pump pulse induced coherence between the ground state and excited state. In this theoretical study, we apply this technique to the photodissociation dynamics of a pyrrole molecule and demonstrate its capability of probing electronic coherence at a conical intersection as well as population transfer. We demonstrate that a magnetic field can be effectively used to extract novel information about electron and nuclear molecular dynamics.

Effect of meddling ARBs on ARGs dynamics in fungal infested soil and their selective dispersal along spatially distant mycelial networks.

During the recent times, environmental antibiotic resistance genes (ARGs) and their potential transfer to other bacterial hosts of pathogenic importance are of serious concern. However, the dissemination strategies of such ARGs are largely unknown. We tested that saprotrophic soil fungi differentially enriched antibiotic resistant bacteria (ARBs) and subsequently contributed in spatial distribution of selective ARGs. Wafergen qPCR analysis of 295 different ARGs was conducted for manure treated pre-sterilized soil incubated or not with selected bacterial-fungal consortia. The qPCR assay detected unique ARGs specifically found in the mycosphere of ascomycetous and basidiomycetous fungi. Both fungi exerted potentially different selection pressures on ARBs, resulting in different patterns of ARGs dissemination (to distant places) along their respective growing fungal highways. The relative abundance of mobile genetic elements (MGEs) was significantly decreased along fungal highways compared to the respective inoculation points. Moreover, the decrease in MGEs and ARGs (along fungal highways) was more prominent over time which depicts the continuous selection pressure of growing fungi on ARBs for enrichment of particular ARGs in mycosphere. Such data also indicate the potential role of saprotrophic soil fungi to facilitate horizontal gene transfer within mycospheric environmental settings. Our study, therefore, advocates to emphasize the future investigations for such (bacteria-fungal) interactive microbial consortia for potential (spatial) dissemination of resistance determinants which may ultimately increase the exposure risks of ARGs.

Synthesis of curcumin derivatives targeting androgen receptor for castration-resistant prostate cancer therapy.

In this work, a series of curcumin derivatives (1a-1h, 2a-2g, and 3a-3c) were synthesized for the suppression of castration-resistant prostate cancer cells. All synthesized compounds were characterized by 1H NMR, 13C NMR, HRMS, and melting point. The in vitro cytotoxicity study shows that compounds 1a, 1e, 1f, 1h, 2g, 3a, and 3c display similar or enhanced cytotoxicity against 22Rv1 and C4-2 cells as compared to ASC-J9, other synthesized compounds display reduced cytotoxicity against 22Rv1 and C4-2 cells as compared to ASC-J9. Molecular docking simulation was performed to study the binding affinity and probable binding modes of the synthesized compounds with androgen receptor. The results show that all synthesized compounds exhibit higher cdocker interaction energies as compared to ASC-J9. Compounds 1h, 2g, and 3c not only show strong cytotoxicity against 22Rv1 and C4-2 cells but also exhibit high binding affinity with androgen receptor. In androgen receptor suppression study, compounds 1f and 2g show similar androgen receptor suppression effect as compared to ASC-J9 on C4-2 cells, compound 3c displays significantly enhanced AR suppression effect as compared to ASC-J9, 1f and 2g. Compounds 1a, 1e, 1f, 1h, 2g, 3a and 3c prepared in this work have significant potential for castration-resistant prostate cancer therapy.

Red blood cell count in cerebrospinal fluid was correlated with inflammatory markers on the seventh postoperative day and all associated with the outcome of aneurysmal subarachnoid hemorrhage patients.

Background: Exploring factors associated with the outcome of patients with aneurysmal subarachnoid hemorrhage (aSAH) has become a hot focus in research. We sought to investigate the associations of inflammatory markers and blood cell count in cerebrospinal fluid with the outcome of aSAH patients. Methods: We carried a retrospective study including 200 patients with aSAH and surgeries. The associations of neutrophil, lymphocyte, neutrophil-lymphocyte ratio (NLR), platelet-lymphocyte ratio (PLR), systemic immune inflammation index (SII), system inflammation response index (SIRI), and blood cell count in cerebrospinal fluid on the 1st and 7th postoperative days with the outcome of aSAH patients were investigated by univariate analysis and multivariate logistic regression model. Results: According to the modified Rankin scale (mRS) score, there were 147 patients with good outcome and 53 patients with poor outcome. The neutrophil, NLR, SIRI, and SII levels on the seventh postoperative day in patients with poor outcome were all significantly higher than patients with good outcome, P < 0.05. The multivariate logistic regression model including inflammatory markers and blood cell counts in cerebrospinal fluid on the 1st postoperative day confirmed that red blood cell count in cerebrospinal fluid (≥177 × 109/L; OR: 7.227, 95% CI: 1.160-45.050, P = 0.034) was possibly associated with poor outcome of aSAH patients, surgical duration (≥169 min), Fisher grade (III-IV), hypertension, and infections were also possibly associated with the poor outcome. The model including inflammatory markers and blood cell counts in cerebrospinal fluid on the 7th postoperative day confirmed that red blood cell count in cerebrospinal fluid (≥54 × 109/L; OR: 39.787, 95% CI: 6.799-232.836, P < 0.001) and neutrophil-lymphocyte ratio (≥8.16; OR: 6.362, 95% CI: 1.424-28.428, P = 0.015) were all possibly associated with poor outcome of aSAH patients. The NLR (r = 0.297, P = 0.007) and SIRI (r = 0.325, P = 0.003) levels were all correlated with the count of red blood cells in cerebrospinal fluid. Discussion: Higher neutrophil-lymphocyte ratio and higher red blood cell count in cerebrospinal fluid were all possibly associated with poor outcome of patients with aneurysmal subarachnoid hemorrhage. However, we need a larger sample study.

Nitrogenous fertilizer plays a more important role than cultivars in shaping sorghum-associated microbiomes.

The plant microbiome plays a crucial role in facilitating plant growth through enhancing nutrient cycling, acquisition and transport, as well as alleviating stresses induced by nutrient limitations. Despite its significance, the relative importance of common agronomic practices, such as nitrogenous fertilizer, in shaping the plant microbiome across different cultivars remains unclear. This study investigated the dynamics of bacterial and fungal communities in leaf, root, rhizosphere, and bulk soil in response to nitrogenous fertilizer across ten sorghum varieties, using 16S rRNA and ITS gene amplicon sequencing, respectively. Our results revealed that nitrogen addition had a greater impact on sorghum-associated microbial communities compared to cultivar. Nitrogen addition significantly reduced bacterial diversity in all compartments except for the root endophytes. However, N addition significantly increased fungal diversity in both rhizosphere and bulk soils, while significantly reducing fungal diversity in the root endophytes. Furthermore, N addition significantly altered the community composition of bacteria and fungi in all four compartments, while cultivars only affected the community composition of root endosphere bacteria and fungi. Network analysis revealed that fertilization significantly reduced microbial network complexity and increased fungal-related network complexity. Collectively, this study provides empirical evidence that sorghum-associated microbiomes are predominantly shaped by nitrogenous fertilizer rather than by cultivars, suggesting that consistent application of nitrogenous fertilizer will ultimately alter plant-associated microbiomes regardless of cultivar selection.

An automated two-stage approach to kidney and tumor segmentation in CT imaging.

BACKGROUND: The incidence of kidney tumors is progressively increasing each year. The precision of segmentation for kidney tumors is crucial for diagnosis and treatment. OBJECTIVE: To enhance accuracy and reduce manual involvement, propose a deep learning-based method for the automatic segmentation of kidneys and kidney tumors in CT images. METHODS: The proposed method comprises two parts: object detection and segmentation. We first use a model to detect the position of the kidney, then narrow the segmentation range, and finally use an attentional recurrent residual convolutional network for segmentation. RESULTS: Our model achieved a kidney dice score of 0.951 and a tumor dice score of 0.895 on the KiTS19 dataset. Experimental results show that our model significantly improves the accuracy of kidney and kidney tumor segmentation and outperforms other advanced methods. CONCLUSION: The proposed method provides an efficient and automatic solution for accurately segmenting kidneys and renal tumors on CT images. Additionally, this study can assist radiologists in assessing patients' conditions and making informed treatment decisions.

A novel microRNA miR-4433a-3p as a potential diagnostic biomarker for lung adenocarcinoma.

Background: Lung adenocarcinoma is one of the leading causes of cancer-related deaths because of the lack of early specific clinical indicators. MicroRNAs (miRNAs) have become the focus in lung cancer diagnosis. Further studies are required to explore miRNA expression in the serum of lung adenocarcinoma patients and their correlation with therapy and analyse specific messenger RNA targets to improve the specificity and sensitivity of early diagnosis. Methods: The Toray 3D-Gene miRNA array was used to compare the expression levels of various miRNAs in the sera of patients with lung adenocarcinoma and healthy volunteers. Highly expressed miRNAs were selected for further analysis. To verify the screening results, serum and pleural fluid samples were analysed using qRT-PCR. Serum levels of the miRNAs and their correlation with the clinical information of patients with lung adenocarcinoma were analysed. The functions of miRNAs were further analysed using the Kyoto Encyclopedia of Gene and Genomes and Gene Ontology databases. Results: Microarray analysis identified 60 and 50 miRNAs with upregulated and downregulated expressions, respectively, in the serum of patients with lung adenocarcinoma compared to those in healthy individuals. Using qRT-qPCR to detection of miRNAs expression in the serum or pleural effusion of patients with early and advanced lung adenocarcinoma, we found that miR-4433a-3p could be used as a diagnostic marker and therapeutic evaluation indicator for lung adenocarcinoma. Serum of miR-4433a-3p levels significantly correlated with the clinical stage. miR-4433a-3p may be more suitable than other tumour markers for the early diagnosis and evaluation of therapeutic effects in lung adenocarcinoma. miR-4433a-3p may affect tumour growth and metastasis by acting on target genes (PIK3CD, UBE2J2, ICMT, PRDM16 and others) and regulating tumour-related signalling pathways (MAPK signal pathway, Ras signalling pathway and others). Conclusion: miR-4433a-3p may serve as a biomarker for the early diagnosis of lung adenocarcinoma and monitoring of therapeutic effects.

Indocyanine green-mediated fabrication of urchin-like hydroxyethyl starch nanocarriers for enhanced drug tumor EPR and deep penetration effects.

Effective EPR and tumor penetration are bottlenecks in current nanomedicine therapy. Comosol software was utilized to analyze the motion process of nanoparticles (NPs) with different shapes, from blood vessels to tumor tissue, to address this. By calculation, urchin-like NPs experienced higher drag forces than spherical NPs, facilitating their EPR and tumor penetration effects. Thus, urchin-like indocyanine green-loaded hydroxyethyl starch-cholesterol (ICG@HES-CH) NPs were prepared by leveraging the instability of ICG responding to near-infrared light (NIR). Upon NIR exposure, ICG degraded and partly disintegrated ICG@HES-CH NPs, and its morphology transformed from spherical to urchin-like. Vincristine (VC), as a model drug, was loaded in urchin-like ICG@HES-CH NPs for the treatment of lymphoma. A20 lymphoma cells and 3T3-A20 tumor organoids were employed to investigate the influence of shape on NPs' cellular uptake, penetration pathway, and cytotoxicity. It demonstrated that urchin-like ICG@HES-CH NPs mainly transport across the extracellular matrix through intercellular pathways, easily reaching the deep tumor sites and achieving higher cytotoxicity. In vivo VC distribution and anti-tumor results indicated that urchin-like NPs increased VC EPR and penetration ability, lowering VC neurotoxicity and superior anti-tumor effect. Therefore, urchin-like ICG@HES-CH NPs have great translational potential to be used as chemotherapeutic nanocarriers in anticancer therapy.

Danger in the Dark: Stability of Perovskite Solar Cells with Varied Stoichiometries and Morphologies Stressed at Various Conditions.

The long-term stability of perovskite solar cells (PSCs) remains a bottleneck for commercialization. While studies on the stoichiometry and morphology of PSCs with regard to performance are prevalent, understanding the influence of these factors on their long-term stability is lacking. In this work, we evaluate the impact of stoichiometry and morphology on the long-term stability of cesium formamidinium-based PSCs. We demonstrate that the lead iodide (PbI2) to formamidinium iodide (FAI) ratio influences stability under various stress factors (elevated temperature and light). A high molar ratio (PbI2/FAI > 1.1) in the perovskite precursor displays drastic degradation under ISOS-L1 (100 mW/cm2, 25 °C, maximum power point tracking) conditions. However, postdegradation analysis contradicts these results. Devices with PbI2/FAI ≤ 1.1 are stable under light, but intermittent current density-voltage characterizations indicate that device performance decreases during storage in the dark. Migration of iodide (I-) ions to the electron-transport layer (ETL) and iodine vacancies (VI-+) to the hole-transport layer (HTL) forms localized shunts in the absorber layer. Pinhole formation, surrounded by FA+-rich regions, explains the extent of damage in comparably aged films. In summary, this work emphasizes the importance of reporting stability under different stress conditions, coupled with postdegradation and dark recovery analyses of PSCs to better understand the complexities of perovskite instability under real-life conditions such as expected during outdoor operation.

Co-delivery of fucoxanthin and Twist siRNA using hydroxyethyl starch-cholesterol self-assembled polymer nanoparticles for triple-negative breast cancer synergistic therapy.

INTRODUCTION: Triple-negative breast cancer (TNBC) represents the most aggressive subtype of breast cancer with an extremely dismal prognosis and few treatment options. As a desmoplastic tumor, TNBC tumor cells are girdled by stroma composed of cancer-associated fibroblasts (CAFs) and their secreted stromal components. The rapidly proliferating tumor cells, together with the tumor stroma, exert additional solid tissue pressure on tumor vasculature and surrounding tissues, severely obstructing therapeutic agent from deep intratumoral penetration, and resulting in tumor metastasis and treatment resistance. OBJECTIVES: Fucoxanthin (FX), a xanthophyll carotenoid abundant in marine algae, has attracted widespread attention as a promising alternative candidate for tumor prevention and treatment. Twist is a pivotal regulator of epithelial to mesenchymal transition, and its depletion has proven to sensitize antitumor drugs, inhibit metastasis, reduce CAFs activation and the following interstitial deposition, and increase tumor perfusion. The nanodrug delivery system co-encapsulating FX and nucleic acid drug Twist siRNA (siTwist) was expected to form a potent anti-TNBC therapeutic cyclical feedback loop. METHODS AND RESULTS: Herein, our studies constituted a novel self-assembled polymer nanomedicine (siTwist/FX@HES-CH) based on the amino-modified hydroxyethyl starch (HES-NH2) grafted with hydrophobic segment cholesterol (CH). The MTT assay, flow cytometry apoptosis analysis, transwell assay, western blot, and 3D multicellular tumor spheroids growth inhibition assay all showed that siTwist/FX@HES-CH could kill tumor cells and inhibit their metastasis in a synergistic manner. The in vivo anti-TNBC efficacy was demonstrated that siTwist/FX@HES-CH remodeled tumor microenvironment, facilitated interstitial barrier crossing, killed tumor cells synergistically, drastically reduced TNBC orthotopic tumor burden and inhibited lung metastasis. CONCLUSION: Systematic studies revealed that this dual-functional nanomedicine that targets both tumor cells and tumor microenvironment significantly alleviates TNBC orthotopic tumor burden and inhibits lung metastasis, establishing a new paradigm for TNBC therapy.

Triple-junction perovskite-perovskite-silicon solar cells with power conversion efficiency of 24.4.

The recent tremendous progress in monolithic perovskite-based double-junction solar cells is just the start of a new era of ultra-high-efficiency multi-junction photovoltaics. We report on triple-junction perovskite-perovskite-silicon solar cells with a record power conversion efficiency of 24.4%. Optimizing the light management of each perovskite sub-cell (∼1.84 and ∼1.52 eV for top and middle cells, respectively), we maximize the current generation up to 11.6 mA cm-2. Key to this achievement was our development of a high-performance middle perovskite sub-cell, employing a stable pure-α-phase high-quality formamidinium lead iodide perovskite thin film (free of wrinkles, cracks, and pinholes). This enables a high open-circuit voltage of 2.84 V in a triple junction. Non-encapsulated triple-junction devices retain up to 96.6% of their initial efficiency if stored in the dark at 85 °C for 1081 h.

Inkjet-printed optical interference filters.

Optical interference filters (OIFs) are vital components for a wide range of optical and photonic systems. They are pivotal in controlling spectral transmission and reflection upon demand. OIFs rely on optical interference of the incident wave at multilayers, which are fabricated with nanometer precision. Here, we demonstrate that these requirements can be fulfilled by inkjet printing. This versatile technology offers a high degree of freedom in manufacturing, as well as cost-affordable and rapid-prototyping features from the micron to the meter scale. In this work, via rational ink design and formulation, OIFs were fully inkjet printed in ambient conditions. Longpass, shortpass, bandpass, and dichroic OIFs were fabricated, and precise control of the spectral response in OIFs was realized. Subsequently, customized lateral patterning of OIFs by inkjet printing was achieved. Furthermore, upscaling of the printed OIFs to A4 size (29.7 × 21.0 cm²) was demonstrated.

US-based Sequential Algorithm Integrating an AI Model for Advanced Liver Fibrosis Screening.

Background Noninvasive tests can be used to screen patients with chronic liver disease for advanced liver fibrosis; however, the use of single tests may not be adequate. Purpose To construct sequential clinical algorithms that include a US deep learning (DL) model and compare their ability to predict advanced liver fibrosis with that of other noninvasive tests. Materials and Methods This retrospective study included adult patients with a history of chronic liver disease or unexplained abnormal liver function test results who underwent B-mode US of the liver between January 2014 and September 2022 at three health care facilities. A US-based DL network (FIB-Net) was trained on US images to predict whether the shear-wave elastography (SWE) value was 8.7 kPa or higher, indicative of advanced fibrosis. In the internal and external test sets, a two-step algorithm (Two-step#1) using the Fibrosis-4 Index (FIB-4) followed by FIB-Net and a three-step algorithm (Three-step#1) using FIB-4 followed by FIB-Net and SWE were used to simulate screening scenarios where liver stiffness measurements were not or were available, respectively. Measures of diagnostic accuracy were calculated using liver biopsy as the reference standard and compared between FIB-4, SWE, FIB-Net, and European Association for the Study of the Liver guidelines (ie, FIB-4 followed by SWE), along with sequential algorithms. Results The training, validation, and test data sets included 3067 (median age, 42 years [IQR, 33-53 years]; 2083 male), 1599 (median age, 41 years [IQR, 33-51 years]; 1124 male), and 1228 (median age, 44 years [IQR, 33-55 years]; 741 male) patients, respectively. FIB-Net obtained a noninferior specificity with a margin of 5% (P < .001) compared with SWE (80% vs 82%). The Two-step#1 algorithm showed higher specificity and positive predictive value (PPV) than FIB-4 (specificity, 79% vs 57%; PPV, 44% vs 32%) while reducing unnecessary referrals by 42%. The Three-step#1 algorithm had higher specificity and PPV compared with European Association for the Study of the Liver guidelines (specificity, 94% vs 88%; PPV, 73% vs 64%) while reducing unnecessary referrals by 35%. Conclusion A sequential algorithm combining FIB-4 and a US DL model showed higher diagnostic accuracy and improved referral management for all-cause advanced liver fibrosis compared with FIB-4 or the DL model alone. © RSNA, 2024 Supplemental material is available for this article. See also the editorial by Ghosh in this issue.

Microbial species pool-mediated diazotrophic community assembly in crop microbiomes during plant development.

Plant-associated diazotrophs strongly relate to plant nitrogen (N) supply and growth. However, our knowledge of diazotrophic community assembly and microbial N metabolism in plant microbiomes is largely limited. Here we examined the assembly and temporal dynamics of diazotrophic communities across multiple compartments (soils, epiphytic and endophytic niches of root and leaf, and grain) of three cereal crops (maize, wheat, and barley) and identified the potential N-cycling pathways in phylloplane microbiomes. Our results demonstrated that the microbial species pool, influenced by site-specific environmental factors (e.g., edaphic factors), had a stronger effect than host selection (i.e., plant species and developmental stage) in shaping diazotrophic communities across the soil-plant continuum. Crop diazotrophic communities were dominated by a few taxa (~0.7% of diazotrophic phylotypes) which were mainly affiliated with Methylobacterium, Azospirillum, Bradyrhizobium, and Rhizobium. Furthermore, eight dominant taxa belonging to Azospirillum and Methylobacterium were identified as keystone diazotrophic taxa for three crops and were potentially associated with microbial network stability and crop yields. Metagenomic binning recovered 58 metagenome-assembled genomes (MAGs) from the phylloplane, and the majority of them were identified as novel species (37 MAGs) and harbored genes potentially related to multiple N metabolism processes (e.g., nitrate reduction). Notably, for the first time, a high-quality MAG harboring genes involved in the complete denitrification process was recovered in the phylloplane and showed high identity to Pseudomonas mendocina. Overall, these findings significantly expand our understanding of ecological drivers of crop diazotrophs and provide new insights into the potential microbial N metabolism in the phyllosphere.IMPORTANCEPlants harbor diverse nitrogen-fixing microorganisms (i.e., diazotrophic communities) in both belowground and aboveground tissues, which play a vital role in plant nitrogen supply and growth promotion. Understanding the assembly and temporal dynamics of crop diazotrophic communities is a prerequisite for harnessing them to promote plant growth. In this study, we show that the site-specific microbial species pool largely shapes the structure of diazotrophic communities in the leaves and roots of three cereal crops. We further identify keystone diazotrophic taxa in crop microbiomes and characterize potential microbial N metabolism pathways in the phyllosphere, which provides essential information for developing microbiome-based tools in future sustainable agricultural production.

Collaborative Enhancement of Consistency and Accuracy in US Diagnosis of Thyroid Nodules Using Large Language Models.

Background Large language models (LLMs) hold substantial promise for medical imaging interpretation. However, there is a lack of studies on their feasibility in handling reasoning questions associated with medical diagnosis. Purpose To investigate the viability of leveraging three publicly available LLMs to enhance consistency and diagnostic accuracy in medical imaging based on standardized reporting, with pathology as the reference standard. Materials and Methods US images of thyroid nodules with pathologic results were retrospectively collected from a tertiary referral hospital between July 2022 and December 2022 and used to evaluate malignancy diagnoses generated by three LLMs-OpenAI's ChatGPT 3.5, ChatGPT 4.0, and Google's Bard. Inter- and intra-LLM agreement of diagnosis were evaluated. Then, diagnostic performance, including accuracy, sensitivity, specificity, and area under the receiver operating characteristic curve (AUC), was evaluated and compared for the LLMs and three interactive approaches: human reader combined with LLMs, image-to-text model combined with LLMs, and an end-to-end convolutional neural network model. Results A total of 1161 US images of thyroid nodules (498 benign, 663 malignant) from 725 patients (mean age, 42.2 years ± 14.1 [SD]; 516 women) were evaluated. ChatGPT 4.0 and Bard displayed substantial to almost perfect intra-LLM agreement (κ range, 0.65-0.86 [95% CI: 0.64, 0.86]), while ChatGPT 3.5 showed fair to substantial agreement (κ range, 0.36-0.68 [95% CI: 0.36, 0.68]). ChatGPT 4.0 had an accuracy of 78%-86% (95% CI: 76%, 88%) and sensitivity of 86%-95% (95% CI: 83%, 96%), compared with 74%-86% (95% CI: 71%, 88%) and 74%-91% (95% CI: 71%, 93%), respectively, for Bard. Moreover, with ChatGPT 4.0, the image-to-text-LLM strategy exhibited an AUC (0.83 [95% CI: 0.80, 0.85]) and accuracy (84% [95% CI: 82%, 86%]) comparable to those of the human-LLM interaction strategy with two senior readers and one junior reader and exceeding those of the human-LLM interaction strategy with one junior reader. Conclusion LLMs, particularly integrated with image-to-text approaches, show potential in enhancing diagnostic medical imaging. ChatGPT 4.0 was optimal for consistency and diagnostic accuracy when compared with Bard and ChatGPT 3.5. © RSNA, 2024 Supplemental material is available for this article.

Total metagenomes outperform viromes in recovering viral diversity from sulfuric soils.

Recent metagenomic advancements have offered unprecedented insights into soil viral ecology. However, it remains a challenge to select the suitable metagenomic method for investigating soil viruses under different environmental conditions. Here, we assessed the performance of viral size-fraction metagenomes (viromes) and total metagenomes in capturing viral diversity from hypersulfidic soils with neutral pH and sulfuric soils with pH <3.3. Viromes effectively enhanced the sequencing coverage of viral genomes in both soil types. Viomes of hypersulfidic soils outperformed total metagenomes by recovering a significantly higher number of viral operational taxonomic units (vOTUs). However, total metagenomes of sulfuric soils recovered ~4.5 times more vOTUs than viromes on average. Altogether, our findings suggest that the choice between viromes and total metagenomes for studying soil viruses should be carefully considered based on the specific environmental conditions.

Biotin-new indocyanine green conjugate: Synthesis, in vitro photocytotoxicity and in vivo biodistribution.

New indocyanine green (ICG) (IR820) is one of the ICG derivatives and attracts increasing attention for cancer management. However, the unsatisfactory tumor targeting ability of IR820 significantly limits its applications for cancer theranostics. Biotin receptor is overexpressed on the membrane of various tumor cells and biotin modified nanocarriers have been reported to enhance the tumor targeting ability on several tumor types. In this work, biotin-new ICG conjugate (Biotin-SS-IR820) was prepared for tumor-targeted IR820 delivery. Biotin and IR820 were coupled through cystamine. The synthesized Biotin-SS-IR820 was characterized by 1 H NMR, FT-IR and HRMS. The in vitro singlet oxygen generation study shows that Biotin-SS-IR820 exhibits similar singlet oxygen generation as compared to IR820 upon 660 nm laser irradiation (0.8 W/cm2 ). The cellular uptake study shows that Biotin-SS-IR820 shows enhanced cellular uptake amount as compared to IR820 on 4T1 cells. As a result, Biotin-SS-IR820 displays enhanced in vitro photodynamic therapeutic effect against 4T1 cells as compared to IR820. In in vivo biodistribution study, Biotin-SS-IR820 shows enhanced tumor accumulation as compared to IR820. Biotin-SS-IR820 developed in this work shows promising prospects for targeted delivery of IR820 to biotin receptor overexpressed tumors.

Two-Dimensional SEC-SEC-UV-MALS-dRI Workflow for Streamlined Analysis and Characterization of Biopharmaceuticals.

The emergence of complex biological modalities in the biopharmaceutical industry entails a significant expansion of the current analytical toolbox to address the need to deploy meaningful and reliable assays at an unprecedented pace. Size exclusion chromatography (SEC) is an industry standard technique for protein separation and analysis. Some constraints of traditional SEC stem from its restricted ability to resolve complex mixtures and notoriously long run times while also requiring multiple offline separation conditions on different pore size columns to cover a wider molecular size distribution. Two-dimensional liquid chromatography (2D-LC) is becoming an important tool not only to increase peak capacity but also to tune selectivity in a single online method. Herein, an online 2D-LC framework in which both dimensions utilize SEC columns with different pore sizes is introduced with a goal to increase throughput for biomolecule separation and characterization. In addition to improving the separation of closely related species, this online 2D SEC-SEC approach also facilitated the rapid analysis of protein-based mixtures of a wide molecular size range in a single online experimental run bypassing time-consuming deployment of different offline SEC methods. By coupling the second dimension with multiangle light scattering (MALS) and differential refractive index (dRI) detectors, absolute molecular weights of the separated species were obtained without the use of calibration curves. As illustrated in this report for protein mixtures and vaccine processes, this workflow can be used in scenarios where rapid development and deployment of SEC assays are warranted, enabling bioprocess monitoring, purity assessment, and characterization.

Synthesis and in vitro antitumor activity of galactosamine-docetaxel conjugates.

Docetaxel (DTX) is a semi-synthetic analogue of paclitaxel which has attracted extensive attention in the treatment of cancer. However, the current clinically used DTX formulations display low tumor targeting ability, leading to unsatisfactory therapeutic outcomes with adverse effects, which poses significant challenges to the clinical application. In this study, three galactosamine (Gal) and docetaxel conjugates with different linkers were synthesized, namely DTX-(suc-Gal)2, DTX-(DTDPA-Gal)2, and DTX-(DSeDPA-Gal)2. These three conjugates were characterized by 1H NMR, FT-IR and HRMS. The in vitro drug release study shows that DTX-(DTDPA-Gal)2 and DTX-(DSeDPA-Gal)2 exhibit glutathione (GSH)-responsive drug release and DTX-(DSeDPA-Gal)2 displays higher GSH-responsiveness. The in vitro antitumor activity study shows that DTX-(DTDPA-Gal)2 and DTX-(DSeDPA-Gal)2 exhibit enhanced cytotoxicity, cell apoptosis rate and G2/M phase arrest against HepG2 cells as compared to DTX-(suc-Gal)2, DTX-(DSeDPA-Gal)2 displays the highest cytotoxicity, cell apoptosis rate and G2/M phase arrest among these three conjugates. In addition, DTX-(DSeDPA-Gal)2 exhibits higher selectivity to HepG2 cells as compared to free DTX. The DTX-(DSeDPA-Gal)2 developed in this study has been proven to be an effective DTX conjugate for selective killing hepatoma cells.

Lipid Isobar and Isomer Imaging Using Nanospray Desorption Electrospray Ionization Combined with Triple Quadrupole Mass Spectrometry.

Mass spectrometry imaging (MSI) is widely used for examining the spatial distributions of molecules in biological samples. Conventional MSI approaches, in which molecules extracted from the sample are distinguished based on their mass-to-charge ratio, cannot distinguish between isomeric species and some closely spaced isobars. To facilitate isobar separation, MSI is typically performed using high-resolution mass spectrometers. Nevertheless, the complexity of the mixture of biomolecules observed in each pixel of the image presents a challenge, even for modern mass spectrometers with the highest resolving power. Herein, we implement nanospray desorption electrospray ionization (nano-DESI) MSI on a triple quadrupole (QqQ) mass spectrometer for the spatial mapping of isobaric and isomeric species in biological tissues. We use multiple reaction monitoring acquisition mode (MRM) with unit mass resolution to demonstrate the performance of this new platform by imaging lipids in mouse brain and rat kidney tissues. We demonstrate that imaging in MRM mode may be used to distinguish between isobaric phospholipids requiring a mass resolving power of 3,800,000. Additionally, we have been able to image eicosanoid isomers, a largely unexplored class of signaling molecules present in tissues at low concentrations, in rat kidney tissue. This new capability substantially enhances the specificity and selectivity of MSI, enabling spatial localization of species that remain unresolved in conventional MSI experiments.