Added value of dynamic contrast-enhanced MR imaging in deep learning-based prediction of local recurrence in grade 4 adult-type diffuse gliomas patients

Local recurrences in patients with grade 4 adult-type diffuse gliomas mostly occur within residual non-enhancing T2 hyperintensity areas after surgical resection. Unfortunately, it is challenging to distinguish non-enhancing tumors from edema in the non-enhancing T2 hyperintensity areas using conventional MRI alone. Quantitative DCE MRI parameters such as Ktrans and Ve convey permeability information of glioblastomas that cannot be provided by conventional MRI. We used the publicly available nnU-Net to train a deep learning model that incorporated both conventional and DCE MRI to detect the subtle difference in vessel leakiness due to neoangiogenesis between the non-recurrence area and the local recurrence area, which contains a higher proportion of high-grade glioma cells. We found that the addition of Ve doubled the sensitivity while nonsignificantly decreasing the specificity for prediction of local recurrence in glioblastomas, which implies that the combined model may result in fewer missed cases of local recurrence. The deep learning model predictive of local recurrence may enable risk-adapted radiotherapy planning in patients with grade 4 adult-type diffuse gliomas.

P- and N-type InAs nanocrystals with innately controlled semiconductor polarity

InAs semiconductor nanocrystals (NCs) exhibit intriguing electrical/optoelectronic properties suitable for next-generation electronic devices. Although there is a need for both n- and p-type semiconductors in such devices, InAs NCs typically exhibit only n-type characteristics. Here, we report InAs NCs with controlled semiconductor polarity. Both p- and n-type InAs NCs can be achieved from the same indium chloride and aminoarsine precursors but by using two different reducing agents, diethylzinc for p-type and diisobutylaluminum hydride for n-type NCs, respectively. This is the first instance of semiconductor polarity control achieved at the synthesis level for InAs NCs and the entire semiconductor nanocrystal systems. Comparable field-effective mobilities for holes (3.3 × 10-3 cm2/V·s) and electrons (3.9 × 10-3 cm2/V·s) are achieved from the respective NC films. The mobility values allow the successful fabrication of complementary logic circuits, including NOT, NOR, and NAND comprising photopatterned p- and n-channels based on InAs NCs.

Increased interleukin-6/C-reactive protein levels are associated with the upregulation of the adenosine pathway and serve as potential markers of therapeutic resistance to immune checkpoint inhibitor-based therapies in non-small cell lung cancer

BACKGROUND

Systemic immune activation, hallmarked by C-reactive protein (CRP) and interleukin-6 (IL-6), can modulate antitumor immune responses. In this study, we evaluated the role of IL-6 and CRP in the stratification of patients with non-small cell lung cancer (NSCLC) treated with immune checkpoint inhibitors (ICIs). We also interrogated the underlying immunosuppressive mechanisms driven by the IL-6/CRP axis.

METHODS

In cohort A (n=308), we estimated the association of baseline CRP with objective response rate (ORR), progression-free survival (PFS), and overall survival (OS) in patients with NSCLC treated with ICIs alone or with chemo-immunotherapy (Chemo-ICI). Baseline tumor bulk RNA sequencing (RNA-seq) of lung adenocarcinomas (LUADs) treated with pembrolizumab (cohort B, n=59) was used to evaluate differential expression of purine metabolism, as well as correlate IL-6 expression with PFS. CODEFACS approach was applied to deconvolve cohort B to characterize the tumor microenvironment by reconstructing the cell-type-specific transcriptome from bulk expression. Using the LUAD cohort from The Cancer Genome Atlas (TCGA) we explored the correlation between IL-6 expression and adenosine gene signatures. In a third cohort (cohort C, n=18), plasma concentrations of CRP, adenosine 2a receptor (A2aR), and IL-6 were measured using ELISA.

RESULTS

In cohort A, 67.2% of patients had a baseline CRP≥10 mg/L (CRP-H). Patients with CRP-H achieved shorter OS (8.6 vs 14.8 months; p=0.006), shorter PFS (3.3 vs 6.6 months; p=0.013), and lower ORR (24.7% vs 46.3%; p=0.015). After adjusting for relevant clinical variables, CRP-H was confirmed as an independent predictor of increased risk of death (HR 1.51, 95% CI: 1.09 to 2.11) and lower probability of achieving disease response (OR 0.34, 95% CI: 0.13 to 0.89). In cohort B, RNA-seq analysis demonstrated higher IL-6 expression on tumor cells of non-responders, along with a shorter PFS (p<0.05) and enrichment of the purinergic pathway. Within the TCGA LUAD cohort, tumor IL-6 expression strongly correlated with the adenosine signature (R=0.65; p<2.2e-16). Plasma analysis in cohort C demonstrated that CRP-H patients had a greater median baseline level of A2aR (6.0 ng/mL vs 1.3 ng/mL; p=0.01).

CONCLUSIONS

This study demonstrates CRP as a readily available blood-based prognostic biomarker in ICI-treated NSCLC. Additionally, we elucidate a potential link of the CRP/IL-6 axis with the immunosuppressive adenosine signature pathway that could drive inferior outcomes to ICIs in NSCLC and also offer novel therapeutic avenues.

A quantum-inspired probabilistic prime factorization based on virtually connected Boltzmann machine and probabilistic annealing

Probabilistic computing has been introduced to operate functional networks using a probabilistic bit (p-bit), broadening the computational abilities in non-deterministic polynomial searching operations. However, previous developments have focused on emulating the operation of quantum computers similarly, implementing every p-bit with large weight-sum matrix multiplication blocks and requiring tens of times more p-bits than semiprime bits. In addition, operations based on a conventional simulated annealing scheme required a large number of sampling operations, which deteriorated the performance of the Ising machines. Here we introduce a prime factorization machine with a virtually connected Boltzmann machine and probabilistic annealing method, which are designed to reduce the hardware complexity and number of sampling operations. From 10-bit to 64-bit prime factorizations were performed, and the machine offers up to 1.2 × 108 times improvement in the number of sampling operations compared with previous factorization machines, with a 22-fold smaller hardware resource.

Deep learning based on dynamic susceptibility contrast MR imaging for prediction of local progression in adult-type diffuse glioma (grade 4)

Adult-type diffuse glioma (grade 4) has infiltrating nature, and therefore local progression is likely to occur within surrounding non-enhancing T2 hyperintense areas even after gross total resection of contrast-enhancing lesions. Cerebral blood volume (CBV) obtained from dynamic susceptibility contrast perfusion-weighted imaging (DSC-PWI) is a parameter that is well-known to be a surrogate marker of both histologic and angiographic vascularity in tumors. We built two nnU-Net deep learning models for prediction of early local progression in adult-type diffuse glioma (grade 4), one using conventional MRI alone and one using multiparametric MRI, including conventional MRI and DSC-PWI. Local progression areas were annotated in a non-enhancing T2 hyperintense lesion on preoperative T2 FLAIR images, using the follow-up contrast-enhanced (CE) T1-weighted (T1W) images as the reference standard. The sensitivity was doubled with the addition of nCBV (80% vs. 40%, P = 0.02) while the specificity was decreased nonsignificantly (29% vs. 48%, P = 0.39), suggesting that fewer cases of early local progression would be missed with the addition of nCBV. While the diagnostic performance of CBV model is still poor and needs improving, the multiparametric deep learning model, which presumably learned from the subtle difference in vascularity between early local progression and non-progression voxels within perilesional T2 hyperintensity, may facilitate risk-adapted radiotherapy planning in adult-type diffuse glioma (grade 4) patients.

Near-field infrared nanoscopic study of EUV- and e-beam-exposed hydrogen silsesquioxane photoresist

This article presents a technique of scattering-type scanning near-field optical microscopy (s-SNOM) based on scanning probe microscopy as a nanoscale-resolution chemical visualization technique of the structural changes in photoresist thin films. Chemical investigations were conducted in the nanometer regime by highly concentrated near-field infrared on the sharp apex of the metal-coated atomic force microscopy (AFM) tip. When s-SNOM was applied along with Fourier transform infrared spectroscopy to characterize the extreme UV- and electron-beam (e-beam)-exposed hydrogen silsesquioxane films, line and space patterns of half-pitch 100, 200, 300, and 500 nm could be successfully visualized prior to pattern development in the chemical solutions. The linewidth and line edge roughness values of the exposed domains obtained by s-SNOM were comparable to those extracted from the AFM and scanning electron microscopy images after development. The chemical analysis capabilities provided by s-SNOM provide new analytical opportunities that are not possible with traditional e-beam-based photoresist measurement, thus allowing information to be obtained without interference from non-photoreaction processes such as wet development.

De novo selected hACE2 mimics that integrate hotspot peptides with aptameric scaffolds for binding tolerance of SARS-CoV-2 variants

The frequent occurrence of viral variants is a critical problem in developing antiviral prophylaxis and therapy; along with stronger recognition of host cell receptors, the variants evade the immune system-based vaccines and neutralizing agents more easily. In this work, we focus on enhanced receptor binding of viral variants and demonstrate generation of receptor-mimicking synthetic reagents, capable of strongly interacting with viruses and their variants. The hotspot interaction of viruses with receptor-derived short peptides is maximized by aptamer-like scaffolds, the compact and stable architectures of which can be in vitro selected from a myriad of the hotspot peptide-coupled random nucleic acids. We successfully created the human angiotensin-converting enzyme 2 (hACE2) receptor-mimicking hybrid ligand that recruits the hACE2-derived receptor binding domain-interacting peptide to directly interact with a binding hotspot of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Experiencing affinity boosting by ~500% to Omicron, the de novo selected hACE2 mimic exhibited a great binding tolerance to all SARS-CoV-2 variants of concern.

Understanding the Sidewall Passivation Effects in AlGaInP/GaInP Micro-LED

The passivation effects of sulfur treatment and Al₂O₃ passivation for AlGaInP/GaInP red micro-light-emitting-diodes (LEDs) were investigated in terms of the external quantum efficiency (EQE) and the current density showing the peak EQE (J_{EQE, peak}). We systematically compared the electrical and optical characteristics of the micro-LEDs with and without passivation according to various sizes. Interestingly, our investigation indicated that simple electrical characteristics such as current density-voltage property are difficult to precisely reflect the minor change in electrical properties due to passivation when the device has the inherently low leakage current. Whereas the EQE was enhanced by 20% and J_{EQE, peak} was largely shifted to a lower current density region at the LED with a size of 15 × 15 μm². To examine the passivation effects, we carefully analyzed the EQE and J_{EQE, peak} with the ABC recombination model, and established the methodology to investigate the influence of a sidewall in micro-LEDs. As a result, we extracted the surface recombination velocity regarding the surface passivation, showing a nearly 14% reduction with the passivation.

Electrically driven strain-induced deterministic single-photon emitters in a van der Waals heterostructure

Quantum confinement in transition metal dichalcogenides (TMDCs) enables the realization of deterministic single-photon emitters. The position and polarization control of single photons have been achieved via local strain engineering using nanostructures. However, most existing TMDC-based emitters are operated by optical pumping, while the emission sites in electrically pumped emitters are uncontrolled. Here, we demonstrate electrically driven single-photon emitters located at the positions where strains are induced by atomic force microscope indentation on a van der Waals heterostructure consisting of graphene, hexagonal boron nitride, and tungsten diselenide. The optical, electrical, and mechanical properties induced by the local strain gradient were systematically analyzed. The emission at the indentation sites exhibits photon antibunching behavior with a g⁽²⁾(0) value of ~0.3, intensity saturation, and a linearly cross-polarized doublet, at 4 kelvin. This robust spatial control of electrically driven single-photon emitters will pave the way for the practical implementation of integrated quantum light sources.

Reducing tumor invasiveness by ramucirumab and TGF-β receptor kinase inhibitor in a diffuse-type gastric cancer patient-derived cell model

BACKGROUND

Diffuse-type gastric cancer (GC) is known to be more aggressive and relatively resistant to conventional chemotherapy. Hence, more optimized treatment strategy is urgently needed in diffuse-type GC.

METHODS

Using a panel of 10 GC cell lines and 3 GC patient-derived cells (PDCs), we identified cell lines with high EMTness which is a distinct feature for diffuse-type GC. We treated GC cells with high EMTness with ramucirumab alone, TGF-β receptor kinase inhibitor (TEW-7197) alone, or in combination to investigate the drug's effects on invasiveness, spheroid formation, EMT marker expression, and tumor-induced angiogenesis using a spheroid-on-a-chip model.

RESULTS

Both TEW-7197 and ramucirumab treatments profoundly decreased invasiveness of EMT-high cell lines and PDCs. With a 3D tumor spheroid-on-a-chip, we identified versatile influence of co-treatment on cancer cell-induced blood vessel formation as well as on EMT progression in tumor spheroids. The 3D tumor spheroid-on-a-chip demonstrated that TEW-7197 + ramucirumab combination significantly decreased PDC-induced vessel formation.

CONCLUSIONS

In this study, we showed TEW-7197 and ramucirumab considerably decreased invasiveness, thus EMTness in a panel of diffuse-type GC cell lines including GC PDCs. Taken together, we confirmed that combination of TEW-7197 and ramucirumab reduced tumor spheroid and GC PDC-induced blood vessel formation concomitantly in the spheroid-on-a-chip model.

Nanoparticle-based computing architecture for nanoparticle neural networks

The lack of a scalable nanoparticle-based computing architecture severely limits the potential and use of nanoparticles for manipulating and processing information with molecular computing schemes. Inspired by the von Neumann architecture (VNA), in which multiple programs can be operated without restructuring the computer, we realized the nanoparticle-based VNA (NVNA) on a lipid chip for multiple executions of arbitrary molecular logic operations in the single chip without refabrication. In this system, nanoparticles on a lipid chip function as the hardware that features memory, processors, and output units, and DNA strands are used as the software to provide molecular instructions for the facile programming of logic circuits. NVNA enables a group of nanoparticles to form a feed-forward neural network, a perceptron, which implements functionally complete Boolean logic operations, and provides a programmable, resettable, scalable computing architecture and circuit board to form nanoparticle neural networks and make logical decisions.

Computer-aided discovery of connected metal-organic frameworks

Composite metal-organic frameworks (MOFs) tend to possess complex interfaces that prevent facile and rational design. Here we present a joint computational/experimental workflow that screens thousands of MOFs and identifies the optimal MOF pairs that can seamlessly connect to one another by taking advantage of the fact that the metal nodes of one MOF can form coordination bonds with the linkers of the second MOF. Six MOF pairs (HKUST-1@MOF-5, HKUST-1@IRMOF-18, UiO-67@HKUST-1, PCN-68@MOF-5, UiO-66@MIL-88B(Fe) and UiO-67@MIL-88C(Fe)) yielded from our theoretical predictions were successfully synthesized, leading to clean single crystalline MOF@MOF, demonstrating the power of our joint workflow. Our work can serve as a starting point to accelerate the discovery of novel MOF composites that can potentially be used for many different applications.

Nano-bio-computing lipid nanotablet

Using nanoparticles as substrates for computation enables algorithmic and autonomous controls of their unique and beneficial properties. However, scalable architecture for nanoparticle-based computing systems is lacking. Here, we report a platform for constructing nanoparticle logic gates and circuits at the single-particle level on a supported lipid bilayer. Our "lipid nanotablet" platform, inspired by cellular membranes that are exploited to compartmentalize and control signaling networks, uses a lipid bilayer as a chemical circuit board and nanoparticles as computational units. On a lipid nanotablet, a single-nanoparticle logic gate senses molecules in solution as inputs and triggers particle assembly or disassembly as an output. We demonstrate a set of Boolean logic operations, fan-in/fan-out of logic gates, and a combinational logic circuit such as a multiplexer. We envisage that our approach to modularly implement nanoparticle circuits on a lipid bilayer will create new paradigms and opportunities in molecular computing, nanoparticle circuits, and systems nanoscience.

Poro-elasto-capillary wicking of cellulose sponges

We mundanely observe cellulose (kitchen) sponges swell while absorbing water. Fluid flows in deformable porous media, such as soils and hydrogels, are classically described on the basis of the theories of Darcy and poroelasticity, where the expansion of media arises due to increased pore pressure. However, the situation is qualitatively different in cellulosic porous materials like sponges because the pore expansion is driven by wetting of the surrounding cellulose walls rather than by increase of the internal pore pressure. We address a seemingly so simple but hitherto unanswered question of how fast water wicks into the swelling sponge. Our experiments uncover a power law of the wicking height versus time distinct from that for nonswelling materials. The observation using environmental scanning electron microscopy reveals the coalescence of microscale wall pores with wetting, which allows us to build a mathematical model for pore size evolution and the consequent wicking dynamics. Our study sheds light on the physics of water absorption in hygroscopically responsive multiscale porous materials, which have far more implications than everyday activities (for example, cleaning, writing, and painting) carried out with cellulosic materials (paper and sponge), including absorbent hygiene products, biomedical cell cultures, building safety, and cooking.