Exploring Chemical Reaction Space with Machine Learning Models: Representation and Feature Perspective.

Chemical reactions serve as foundational building blocks for organic chemistry and drug design. In the era of large AI models, data-driven approaches have emerged to innovate the design of novel reactions, optimize existing ones for higher yields, and discover new pathways for synthesizing chemical structures comprehensively. To effectively address these challenges with machine learning models, it is imperative to derive robust and informative representations or engage in feature engineering using extensive data sets of reactions. This work aims to provide a comprehensive review of established reaction featurization approaches, offering insights into the selection of representations and the design of features for a wide array of tasks. The advantages and limitations of employing SMILES, molecular fingerprints, molecular graphs, and physics-based properties are meticulously elaborated. Solutions to bridge the gap between different representations will also be critically evaluated. Additionally, we introduce a new frontier in chemical reaction pretraining, holding promise as an innovative yet unexplored avenue.

Characteristics of second-hand exposure to aerosols from e-cigarettes: A literature review since 2010.

In recent years, the use of electronic vaping products (also named e-cigarettes) has increased due to their appealing flavors and nicotine delivery without the combustion of tobacco. Although the hazardous substances emitted by e-cigarettes are largely found to be much lower than combustible cigarettes, second-hand exposure to e-cigarette aerosols is not completely benign for bystanders. This work reviewed and synthesized findings on the second-hand exposure of aerosols from e-cigarettes and compared the results with those of the combustible cigarettes. In this review, different results were integrated based upon sampling locations such as residences, vehicles, offices, public places, and experimental exposure chambers. In addition, the factors that influence the second-hand exposure levels were identified by objectively reviewing and integrating the impacts of combustible cigarettes and e-cigarettes on the environment. It is a challenge to compare the literature data directly to assess the effect of smoking/vaping on the indoor environment. The room volume, indoor air exchange rate, puffing duration, and puffing numbers should be considered, which are important factors in determining the degree of pollution. Therefore, it is necessary to calculate the "emission rate" to normalize the concentration of pollutants emitted under various experimental conditions and make the results comparable. This review aims to increase the awareness regarding the harmful effects of the second-hand exposure to aerosols coming from the use of cigarettes and e-cigarettes, identify knowledge gaps, and provide a scientific basis for future policy interventions with regard to the regulation of smoking and vaping.

A critical review of research methodologies for COVID-19 transmission in indoor built environment.

The Coronavirus Disease 2019 (COVID-19) has caused massive losses for the global economy. Scholars have used different methods to study the transmission mode and influencing factors of the virus to find effective methods to provide people with a healthy built environment. However, these studies arrived at different or even contradictory conclusions. This review presents the main research methodologies utilized in this field, summarizes the main investigation methods, and critically discusses their related conclusions. Data statistical analysis, sample collection, simulation models, and replication transmission scenarios are the main research methods. The summarized conclusion for prevention from all reviewed papers are: adequate ventilation and proper location of return air vents, proper use of personal protective equipment, as well as the reasonable and strict enforcement of policies are the main methods for reducing the transmission. Recommendations including standardized databases, causation clarification, rigorous experiment design, improved simulation accuracy and verification are provided.

The characteristics of particulate matter in different subway station environmental control systems.

Particulate matter (PM2.5, PM10) in urban subway stations can significantly impact passengers' health. The particle concentration in subway stations is influenced by many factors. However, few existing studies have explored the impact of environmental control systems in-depth, especially under different outdoor pollution conditions. To address this research gap, this study focused on measuring and comparing the characteristics of PM2.5 and PM10 at subway stations with three control systems (open, closed, and screen door) under varying pollution conditions in Beijing. Particle concentrations from platforms, carriages, and outdoors were monitored and analyzed using statistical methods. The results showed that the particle concentration in the closed system was generally 20-40 µg/m3 higher than that in the screen system at the platform, which might be attributed to the piston wind, as the air from the tunnel with a lot of dirt. The pollution in the carriage was more severe for the open system than that of the screen system. The PM2.5/PM10 ratio in the carriage was 91%, 90%, and 83.84% for the closed, open, and screen systems, respectively. This indicates that the screen door could reduce the particle concentration in the platform to 10%-50%. The particle concentration varied among subway stations with different environmental control systems, suggesting that the prevention and control strategies for particulate matter pollution should be different for stations with different systems.

The Role of Social Media in Building Pandemic Resilience in an Urban Community: A Qualitative Case Study.

This paper explores the influence of social media in fostering resilience within an urban spatial context, specifically in Bangalore, India, during the COVID-19 lockdown, a period marked by a surge in digital communication due to movement restrictions. To control the rapid spread of the virus, over 1.38 billion people were given stay-at-home orders by the government of India during the onset of the pandemic. The restrictions in movement forced individuals to shift to online modes of connection and communication. As the field of digital epidemiology, that is, the use of digital tools and data to understand and improve health took center stage during the pandemic, the focus shifted towards the social media landscape, which is often associated with its negative aspects, such as misinformation. However, this paper delves into social media's potential to build resilience on a local scale, particularly given its increased usage during the pandemic. Through in-depth online interviews with eight urban residents, we conducted a thematic analysis to understand social media's role during the lockdown. Results indicate that social media facilitated effective information exchange and fostered a sense of community. Furthermore, it engendered an environment conducive to prosocial behavior, a known resilience amplifier. We also highlight the importance of baseline context regarding the users directly engaged in social media data generation with respect to digital epidemiology analytics tools for large-scale social media data and the need for qualitative input feeding into their design. Our study highlights the need for a balanced perspective on social media use in times of crisis, recognizing its potential to boost community resilience in an urban setting, and further enriching digital epidemiology approaches.

Deep learning multi-organ segmentation for whole mouse cryo-images including a comparison of 2D and 3D deep networks.

Cryo-imaging provided 3D whole-mouse microscopic color anatomy and fluorescence images that enables biotechnology applications (e.g., stem cells and metastatic cancer). In this report, we compared three methods of organ segmentation: 2D U-Net with 2D-slices and 3D U-Net with either 3D-whole-mouse or 3D-patches. We evaluated the brain, thymus, lung, heart, liver, stomach, spleen, left and right kidney, and bladder. Training with 63 mice, 2D-slices had the best performance, with median Dice scores of > 0.9 and median Hausdorff distances of < 1.2 mm in eightfold cross validation for all organs, except bladder, which is a problem organ due to variable filling and poor contrast. Results were comparable to those for a second analyst on the same data. Regression analyses were performed to fit learning curves, which showed that 2D-slices can succeed with fewer samples. Review and editing of 2D-slices segmentation results reduced human operator time from ~ 2-h to ~ 25-min, with reduced inter-observer variability. As demonstrations, we used organ segmentation to evaluate size changes in liver disease and to quantify the distribution of therapeutic mesenchymal stem cells in organs. With a 48-GB GPU, we determined that extra GPU RAM improved the performance of 3D deep learning because we could train at a higher resolution.

Magnetic resonance molecular imaging of extradomain B fibronectin enables detection of pancreatic ductal adenocarcinoma metastasis.

Extradomain-B Fibronectin (EDB-FN) is an oncomarker that can be visualized with magnetic resonance molecular imaging (MRMI) to detect pancreatic ductal adenocarcinoma (PDAC) metastasis. In this study, we sought to assess the expression of EDB-FN in clinical samples of PDAC and to evaluate MRMI of PDAC metastasis with an EDB-FN-specific gadolinium-based contrast agent (MT218) in an orthotopic KPC-GFP-Luc mouse model. EDB-FN expression was evaluated in PDAC tissue samples through immunohistochemistry. RNA-Seq data obtained from the GEPIA2 project was evaluated to demonstrate EDB-FN expression in large patient cohorts. FLASH-3D MRI at 3 T of the KPC-GFP-Luc metastasis model was performed following injection of MT218. Tumor enhancement in MR images was correlated to postmortem distribution of KPC-GFP-Luc tumors using fluorescent and bright-field cryo-imaging and anatomical landmarks. EDB-FN immunohistochemical staining scores of human metastatic tumor stroma, (2.17 ± 0.271), metastatic tumor parenchyma (2.08 ± 0.229), primary tumor stroma (1.61 ± 0.26), and primary tumor parenchyma (1.61 ± 0.12) were significantly (p < 0.0001) higher than normal pancreas stroma (0.14 ± 0.10) and normal pancreas parenchyma (0.14 ± 0.14). EDB-FN mRNA expression in tumors is 4.98 log2(TPM + 1) and 0.18 log2(TPM + 1) in normal tissue (p < 0.01). A mouse model of EDB-FN rich PDAC metastasis exhibited T1-weighted contrast to noise (CNR) changes of 21.80 ± 4.34 in perimetastatic regions and 8.38 ± 0.79 in metastatic regions identified through cryo-imaging, significantly higher (p < 0.05) than CNR changes found in normal liver (-6.43 ± 0.92), mesentery (2.24 ± 0.92), spleen (-3.06 ± 2.38) and intestine (1.08 ± 2.15). We conclude that EDB-FN is overexpressed in metastatic and primary PDAC tumors and MRMI with MT218 enables the detection of metastatic and perimetastatic tissues.

Quantitative analysis of metastatic breast cancer in mice using deep learning on cryo-image data.

Cryo-imaging sections and images a whole mouse and provides ~ 120-GBytes of microscopic 3D color anatomy and fluorescence images, making fully manual analysis of metastases an onerous task. A convolutional neural network (CNN)-based metastases segmentation algorithm included three steps: candidate segmentation, candidate classification, and semi-automatic correction of the classification result. The candidate segmentation generated > 5000 candidates in each of the breast cancer-bearing mice. Random forest classifier with multi-scale CNN features and hand-crafted intensity and morphology features achieved 0.8645 ± 0.0858, 0.9738 ± 0.0074, and 0.9709 ± 0.0182 sensitivity, specificity, and area under the curve (AUC) of the receiver operating characteristic (ROC), with fourfold cross validation. Classification results guided manual correction by an expert with our in-house MATLAB software. Finally, 225, 148, 165, and 344 metastases were identified in the four cancer mice. With CNN-based segmentation, the human intervention time was reduced from > 12 to ~ 2 h. We demonstrated that 4T1 breast cancer metastases spread to the lung, liver, bone, and brain. Assessing the size and distribution of metastases proves the usefulness and robustness of cryo-imaging and our software for evaluating new cancer imaging and therapeutics technologies. Application of the method with only minor modification to a pancreatic metastatic cancer model demonstrated generalizability to other tumor models.

Rapid synchronized fabrication of vascularized thermosets and composites.

Bioinspired vascular networks transport heat and mass in hydrogels, microfluidic devices, self-healing and self-cooling structures, filters, and flow batteries. Lengthy, multistep fabrication processes involving solvents, external heat, and vacuum hinder large-scale application of vascular networks in structural materials. Here, we report the rapid (seconds to minutes), scalable, and synchronized fabrication of vascular thermosets and fiber-reinforced composites under ambient conditions. The exothermic frontal polymerization (FP) of a liquid or gelled resin facilitates coordinated depolymerization of an embedded sacrificial template to create host structures with high-fidelity interconnected microchannels. The chemical energy released during matrix polymerization eliminates the need for a sustained external heat source and greatly reduces external energy consumption for processing. Programming the rate of depolymerization of the sacrificial thermoplastic to match the kinetics of FP has the potential to significantly expedite the fabrication of vascular structures with extended lifetimes, microreactors, and imaging phantoms for understanding capillary flow in biological systems.

A Protease-Activated Fluorescent Probe Allows Rapid Visualization of Keratinocyte Carcinoma during Excision.

Keratinocyte carcinomas, including basal and squamous cell carcinomas, are the most common human cancers worldwide. While 75% of all keratinocyte carcinoma (4 million annual cases in the United States) are treated with conventional excision, this surgical modality has much lower cure rates than Mohs micrographic surgery, likely due to the bread-loaf histopathologic assessment that visualizes <1% of the tissue margins. A quenched protease-activated fluorescent probe 6qcNIR, which produces a signal only in the protease-rich tumor microenvironment, was topically applied to 90 specimens ex vivo immediately following excision. "Puzzle-fit" analysis was used to correlate the fluorescent images with histology. Probe-dependent fluorescent images correlated with cancer determined by conventional histology. Point-of-care fluorescent detection of skin cancer had a clinically relevant sensitivity of 0.73 and corresponding specificity of 0.88. Importantly, clinicians were effectively trained to read fluorescent images within 15 minutes with reliability and confidence, resulting in sensitivities of 62%-78% and specificities of 92%-97%. Fluorescent imaging using 6qcNIR allows 100% tumor margin assessment by generating en face images that correlate with histology and may be used to overcome the limitations of conventional bread-loaf histology. The utility of 6qcNIR was validated in a busy real-world clinical setting, and clinicians were trained to effectively read fluorescent margins with a short guided instruction, highlighting clinical adaptability. When used in conventional excision, this approach may result in higher cure rates at a lower cost by allowing same-day reexcision when needed, reducing patient anxiety and improving compliance by expediting postsurgical specimen assessment. SIGNIFICANCE: A fluorescent-probe-tumor-visualization platform was developed and validated in human keratinocyte carcinoma excision specimens that may provide simple, rapid, and global assessment of margins during skin cancer excision, allowing same-day reexcision when needed.

Differential Expression of Nicotine Acetylcholine Receptors Associates with Human Breast Cancer and Mediates Antitumor Activity of αO-Conotoxin GeXIVA.

Nicotinic acetylcholine receptors (nAChRs) are membrane receptors and play a major role in tumorigenesis and cancer progression. Here, we have investigated the differential expression of nAChR subunits in human breast cancer cell lines and breast epithelial cell lines at mRNA and protein levels and the effects of the αO-conotoxin GeXIVA, antagonist of α9α10 nAChR, on human breast cancer cells. Reverse transcription polymerase chain reaction (PCR) demonstrated that all nAChR subunits, except α6, were expressed in the 20 tested cell lines. Real time quantitative PCR (QRT-PCR) suggested that the mRNA of α5, α7, α9 and ß4 nAChR subunits were overexpressed in all the breast cancer cell lines compared with the normal epithelial cell line HS578BST. α9 nAChR was highly expressed in almost all the breast cancer cell lines in comparison to normal cells. The different expression is prominent (p < 0.001) as determined by flow cytometry and Western blotting, except for MDA-MB-453 and HCC1395 cell lines. αO-conotoxin GeXIVA that targeted α9α10 nAChR were able to significantly inhibit breast cancer cell proliferation in vitro and merits further investigation as potential agents for targeted therapy.

Identification of nicotinic acetylcholine receptor subunits in different lung cancer cell lines and the inhibitory effect of alpha-conotoxin TxID on lung cancer cell growth.

Lung cancer is an aggressive tumor with high incidence and mortality rate. There was growing evidence supporting that nicotinic acetylcholine receptors (nAChRs) play vital role inlung cancer development. In this study, the expression of α3, α4, α5, α6, α7, α9, α10, ß2, ß3, ß4 nAChR subunits on protein and mRNA level were studied in A549, NCI-H1299, NCI-H1688, DMS114 and normal human embryonic lung fibroblast (HEL) cell lines by real-time quantitative PCR (qPCR) and Western blot assay respectively. The results indicated that most of these nAChR subunits were expressed in these five cell lines. Compared with normal cells, the expression of α3 and ß4 nAChR subunits were upregulated in A549 and NCI-H1299. Thus, we treated A549 and NCI-H1299 with an antagonist α-conotoxin TxID which potently and selectively blocks α3ß4 nAChRs. TxID treatment could inhibit A549 and NCI-H1299 cell growth and enhance the inhibitory effect of adriamycin when treated simultaneously. To sum up, our study identified the expression of nAChR subunits in different lung cells and the anti-tumor effect of α-conotoxin TxID, which may provide novel strategies for lung cancer therapy.

Degradation kinetics of α-conotoxin TxID.

α-Conotoxin (CTx) TxID is a potent α3ß4 nicotinic acetylcholine receptor (nAChR) antagonist that has been suggested as a potential drug candidate to treat addiction and small cell lung cancer. The function and structure of TxID have been well-studied, but analyses of its stability have not previously been reported. The purpose of this study was to analyze the stability and forced degradation of TxID under various conditions: acid, alkali, water hydrolysis, oxidation, light, thiols, temperature, ionic strength and buffer pH. Different degradation products were formed under various conditions, and the degradation patterns of TxID showed pseudo-first-order kinetics. TxID degraded slowest at pH 3 within a pH range of 2-8. The major degradation products were analyzed using liquid chromatography-tandem mass spectrometry and the activity of the main product with α3ß4 nAChR was analyzed using electrophysiological methods. Our analysis of TxID stability may aid the selection of appropriate conditions for peptide production, packaging and storage.

Cervical Cancer Correlates with the Differential Expression of Nicotinic Acetylcholine Receptors and Reveals Therapeutic Targets.

Nicotinic acetylcholine receptors (nAChRs) are associated with various cancers, but the relation between nAChRs and cervical cancer remains unclear. Therefore, this study investigated the differential expression of nAChR subunits in human cervical cancer cell lines (SiHa, HeLa, and CaSki) and in normal ectocervical cell lines (Ect1/E6E7) at mRNA and protein levels. Two specific nAChR subtype blockers, αO-conotoxin GeXIVA and α-conotoxin TxID, were then selected to treat different human cervical cancer cell lines with specific nAChR subtype overexpression. The results showed that α3, α9, α10, and ß4 nAChR subunits were overexpressed in SiHa cells compared with that in normal cells. α9 and α10 nAChR subunits were overexpressed in CaSki cells. α*-conotoxins that targeted either α9α10 or α3ß4 nAChR were able to significantly inhibit cervical cancer cell proliferation. These findings may provide a basis for new targets for cervical cancer targeted therapy.

Molecular imaging and validation of margins in surgically excised nonmelanoma skin cancer specimens.

In an effort to increase the efficiency and cure rate of nonmelanoma skin cancer (NMSC) excisions, we have developed a point-of-care method of imaging and evaluation of skin cancer margins. We evaluate the skin surgical specimens using a smart, near-infrared probe (6qcNIR) that fluoresces in the presence of cathepsin proteases overexpressed in NMSC. Imaging is done with an inverted, flying-spot fluorescence scanner that reduces scatter, giving a 70% improved step response as compared to a conventional imaging system. We develop a scheme for careful comparison of fluorescent signals to histological annotation, which involves image segmentation, fiducial-based registration, and nonrigid free-form deformation on fluorescence images, corresponding color images, "bread-loafed" tissue images, hematoxylin and eosin (H&E)-stained slides, and pathological annotations. From epidermal landmarks, spatial accuracy in the bulk of the sample is ∼ 500 µ m , which when extrapolated with a linear stretch model, suggests an error at the margin of ∼ 100 µ m , within clinical reporting standards. Cancer annotations on H&E slides are transformed and superimposed on the fluorescence images to generate the final results. Using this methodology, fluorescence cancer signals are generally found to correspond spatially with histological annotations. This method will allow us to accurately analyze molecular probes for imaging skin cancer margins.

Cryo-Imaging and Software Platform for Analysis of Molecular MR Imaging of Micrometastases.

We created and evaluated a preclinical, multimodality imaging, and software platform to assess molecular imaging of small metastases. This included experimental methods (e.g., GFP-labeled tumor and high resolution multispectral cryo-imaging), nonrigid image registration, and interactive visualization of imaging agent targeting. We describe technological details earlier applied to GFP-labeled metastatic tumor targeting by molecular MR (CREKA-Gd) and red fluorescent (CREKA-Cy5) imaging agents. Optimized nonrigid cryo-MRI registration enabled nonambiguous association of MR signals to GFP tumors. Interactive visualization of out-of-RAM volumetric image data allowed one to zoom to a GFP-labeled micrometastasis, determine its anatomical location from color cryo-images, and establish the presence/absence of targeted CREKA-Gd and CREKA-Cy5. In a mouse with >160 GFP-labeled tumors, we determined that in the MR images every tumor in the lung >0.3 mm2 had visible signal and that some metastases as small as 0.1 mm2 were also visible. More tumors were visible in CREKA-Cy5 than in CREKA-Gd MRI. Tape transfer method and nonrigid registration allowed accurate (<11 µm error) registration of whole mouse histology to corresponding cryo-images. Histology showed inflammation and necrotic regions not labeled by imaging agents. This mouse-to-cells multiscale and multimodality platform should uniquely enable more informative and accurate studies of metastatic cancer imaging and therapy.

Microscopic validation of whole mouse micro-metastatic tumor imaging agents using cryo-imaging and sliding organ image registration.

We created a metastasis imaging, analysis platform consisting of software and multi-spectral cryo-imaging system suitable for evaluating emerging imaging agents targeting micro-metastatic tumor. We analyzed CREKA-Gd in MRI, followed by cryo-imaging which repeatedly sectioned and tiled microscope images of the tissue block face, providing anatomical bright field and molecular fluorescence, enabling 3D microscopic imaging of the entire mouse with single metastatic cell sensitivity. To register MRI volumes to the cryo bright field reference, we used our standard mutual information, non-rigid registration which proceeded: preprocess → affine → B-spline non-rigid 3D registration. In this report, we created two modified approaches: mask where we registered locally over a smaller rectangular solid, and sliding organ. Briefly, in sliding organ, we segmented the organ, registered the organ and body volumes separately and combined results. Though sliding organ required manual annotation, it provided the best result as a standard to measure other registration methods. Regularization parameters for standard and mask methods were optimized in a grid search. Evaluations consisted of DICE, and visual scoring of a checkerboard display. Standard had accuracy of 2 voxels in all regions except near the kidney, where there were 5 voxels sliding. After mask and sliding organ correction, kidneys sliding were within 2 voxels, and Dice overlap increased 4%-10% in mask compared to standard. Mask generated comparable results with sliding organ and allowed a semi-automatic process.

MRI detection of breast cancer micrometastases with a fibronectin-targeting contrast agent.

Metastasis is the primary cause of death in breast cancer patients. Early detection of high-risk breast cancer, including micrometastasis, is critical in tailoring appropriate and effective interventional therapies. Increased fibronectin expression, a hallmark of epithelial-to-mesenchymal transition, is associated with high-risk breast cancer and metastasis. We have previously developed a penta-peptide CREKA (Cys-Arg-Glu-Lys-Ala)-targeted gadolinium-based magnetic resonance imaging (MRI) contrast agent, CREKA-Tris(Gd-DOTA)3 (Gd-DOTA (4,7,10-tris(carboxymethyl)-1,4,7,10-tetraazacyclododecyl gadolinium), which binds to fibrin-fibronectin complexes that are abundant in the tumour microenvironment of fast-growing breast cancer. Here we assess the capability of CREKA-Tris(Gd-DOTA)3 to detect micrometastasis with MRI in co-registration with high-resolution fluorescence cryo-imaging in female mice bearing metastatic 4T1 breast tumours. We find that CREKA-Tris(Gd-DOTA)3 provides robust contrast enhancement in the metastatic tumours and enables the detection of micrometastases of size <0.5 mm, extending the detection limit of the current clinical imaging modalities. These results demonstrate that molecular MRI with CREKA-Tris(Gd-DOTA)3 may facilitate early detection of high-risk breast cancer and micrometastasis in the clinic.