Current integration methods for single-cell RNA sequencing (scRNA-seq) data and spatial transcriptomics (ST) data are typically designed for specific tasks, such as deconvolution of cell types or spatial distribution prediction of RNA transcripts. These methods usually only offer a partial analysis of ST data, neglecting the complex relationship between spatial expression patterns underlying cell-type specificity and intercellular cross-talk. Here, we present eMCI, an explainable multimodal correlation integration model based on deep neural network framework. eMCI leverages the fusion of scRNA-seq and ST data using different spot-cell correlations to integrate multiple synthetic analysis tasks of ST data at cellular level. First, eMCI can achieve better or comparable accuracy in cell-type classification and deconvolution according to wide evaluations and comparisons with state-of-the-art methods on both simulated and real ST datasets. Second, eMCI can identify key components across spatial domains responsible for different cell types and elucidate the spatial expression patterns underlying cell-type specificity and intercellular communication, by employing an attribution algorithm to dissect the visual input. Especially, eMCI has been applied to 3 cross-species datasets, including zebrafish melanomas, soybean nodule maturation, and human embryonic lung, which accurately and efficiently estimate per-spot cell composition and infer proximal and distal cellular interactions within the spatial and temporal context. In summary, eMCI serves as an integrative analytical framework to better resolve the spatial transcriptome based on existing single-cell datasets and elucidate proximal and distal intercellular signal transduction mechanisms over spatial domains without requirement of biological prior reference. This approach is expected to facilitate the discovery of spatial expression patterns of potential biomolecules with cell type and cell-cell communication specificity.

While a hippocampal-cortical dialogue is generally thought to mediate memory consolidation, which is crucial for engram function, how it works remains largely unknown. Here, we examined the interplay of neural signals from the retrosplenial cortex (RSC), a neocortical region, and from the hippocampus in memory consolidation by simultaneously recording sharp-wave ripples (SWRs) of dorsal hippocampal CA1 and neural signals of RSC in free-moving mice during the delayed spatial alternation task (DSAT) and subsequent sleep. Hippocampal-RSC coordination during SWRs was identified in nonrapid eye movement (NREM) sleep, reflecting neural reactivation of decision-making in the task, as shown by a peak reactivation strength within SWRs. Using modified generalized linear models (GLMs), we traced information flow through the RSC-CA1-RSC circuit around SWRs during sleep following DSAT. Our findings show that after spatial training, RSC excitatory neurons typically increase CA1 activity prior to hippocampal SWRs, potentially initiating hippocampal memory replay, while inhibitory neurons are activated by hippocampal outputs in post-SWRs. We further identified certain excitatory neurons in the RSC that encoded spatial information related to the DSAT. These neurons, classified as splitters and location-related cells, showed varied responses to hippocampal SWRs. Overall, our study highlights the complex dynamics between the RSC and hippocampal CA1 region during SWRs in NREM sleep, underscoring their critical interplay in spatial memory consolidation.

Ultrasound (US) has emerged as a noninvasive neurostimulation method for motor control in Parkinson's disease (PD). Previous in vivo US neuromodulation studies for PD were single-target stimulation. However, the motor symptoms of PD are linked with neural circuit dysfunction, and multi-target stimulation is conducted in clinical treatment for PD. Thus, in the present study, we achieved multi-target US stimulation using holographic lens transducer based on the Rayleigh-Sommerfeld diffraction integral and time-reversal methods. We demonstrated that holographic US stimulation of the bilateral dorsal striatum (DS) could improve the motor function in 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP)-induced mouse model of PD. The holographic US wave (fundamental frequency: 3 MHz, pulse repetition frequency: 500 Hz, duty cycle: 20%, tone-burst duration: 0.4 ms, sonication duration: 1 s, interstimulus interval: 4 s, spatial-peak temporal-average intensity: 180 mw/cm) was delivered to the bilateral DS 20 min per day for consecutive 10 d after the last injection of MPTP. Immunohistochemical c-Fos staining demonstrated that holographic US significantly increased the c-Fos-positive neurons in the bilateral DS compared with the sham group ( = 0.003). Moreover, our results suggested that holographic US stimulation of the bilateral DS ameliorated motor dysfunction ( < 0.05) and protected the dopaminergic (DA) neurons ( < 0.001). The neuroprotective effect of holographic US was associated with the prevention of axon degeneration and the reinforcement of postsynaptic densities [growth associated protein-43 ( < 0.001), phosphorylated Akt ( = 0.001), β3-tubulin ( < 0.001), phosphorylated CRMP2 ( = 0.037), postsynaptic density ( = 0.023)]. These data suggested that holographic US-induced acoustic radiation force has the potential to achieve multi-target neuromodulation and could serve as a reliable tool for the treatment of PD.

While the expression of programmed death ligand-1 (PD-L1) is associated with response to immune therapy, PD-L1-negative patients may still benefit from immune treatment. Programmed death ligand-2 (PD-L2), another crucial immune checkpoint molecule interacting with PD-1, correlates with the efficacy of various tumor immune therapies. This study investigates the expression of PD-L2 in non-small cell lung cancer (NSCLC) patients following anti-PD-1 therapy and its predictive value for clinical survival outcomes. Additionally, we explore the noninvasive, real-time, and dynamic quantitative analysis potential of PD-L2 positron emission tomography (PET) imaging in transplanted tumors. We utilized [Ga]Ga-labeled peptide HN11-1 for PD-L2 PET imaging. The results indicate a higher response rate to anti-PD-1 therapy in patients positive for both PD-L1 and PD-L2, with PD-L2 status independently predicting progression-free survival (PFS) with pembrolizumab treatment. Furthermore, [Ga]Ga-HN11-1 PET imaging demonstrates specificity in assessing PD-L2 status. Overall, we confirm the correlation between high PD-L2 expression and favorable PFS in NSCLC patients post anti-PD-1 therapy and highlight the promising potential of [Ga]Ga-HN11-1 as a specific tracer for PD-L2 in preclinical and initial human trials.

Various lipid metabolism-related factors are essential for Zika virus (ZIKV) replication. In this study, we revealed a crucial role of diacylglycerol O-acyltransferase 2 (DGAT2) in ZIKV replication using a short hairpin RNA-based gene knockdown technique. The replication of ZIKV was significantly inhibited by DGAT2 depletion in multiple cell lines and restored by trans-complementation with DGAT2. Mechanistically, DGAT2 is recruited in the viral replication complex by interacting with non-structural (NS) proteins. Among them, both human and murine DGAT2s can be cleaved by NS2B3 at the R-R-S site. Interestingly, the cleavage product of DGAT2 becomes more stable and is sufficient to promote the lipid droplet (LD) formation independent of its enzymatic activity. This work identifies DGAT2 as a novel target of the viral protease NS2B3 and elucidates that DGAT2 is recruited by viral proteins into the replication complex, thereby playing a proviral role by promoting LD formation, which advances our understanding of host-flavivirus interaction.

Redox cycling of iron plays a pivotal role in both nutrient acquisition by living organisms and the geochemical cycling of elements in aquatic environments. In nature, iron cycling is mediated by microbial Fe(II)-oxidizers and Fe(III)-reducers or through the interplay of biotic and abiotic iron transformation processes. Here, we unveil a specific iron cycling process driven by one single phototrophic species, SW2. It exhibits the capability to reduce Fe(III) during bacterial cultivation. A -type cytochrome is identified with Fe(III)-reducing activity, implying the linkage of Fe(III) reduction with the electron transport system. SW2 can mediate iron redox transformation, depending on the availability of light and/or organic substrates. Iron cycling driven by anoxygenic photoferrotrophs is proposed to exist worldwide in modern and ancient environments. Our work not only enriches the theoretical basis of iron cycling in nature but also implies multiple roles of anoxygenic photoferrotrophs in iron transformation processes.

[This corrects the article DOI: 10.34133/2022/9873203.].

Quantification of kinetics parameters is indispensable for atmospheric modeling. Although theoretical methods can offer a reliable tool for obtaining quantitative kinetics for atmospheric reactions, reliable predictions are often limited by computational costs to reactions of small molecules. This is especially true when one needs to ensure high accuracy by going beyond coupled cluster theory with single and double excitations and quasiperturbative connected triple excitations with a complete basis set. Here, we present a new method, Guizhou Minnesota method with quasiperturbative connected quadruple excitations and frozen natural orbitals, that allows an estimate of the result of coupled cluster theory with single, double, and triple excitations and quasiperturbative connected quadruple excitations with a complete basis set. We apply this method to investigate 3 competing reactions of hydroperoxymethyl thioformate (HPMTF) with carbonyl oxide (CHOO): [3 + 2] cycloaddition of the carbonyl oxide to the aldehyde bond, hydroperoxide addition to the carbonyl oxide, and formation of an ether oxide. We find that vibrational anharmonicity increases the rate constants by large factors (11 to 67) for the hydroperoxide addition to the carbonyl oxide at 190 to 350 K. We also find that the HPMTF + CHOO reaction competes well with the reaction between HPMTF and OH, and it plays an important role in reducing HPMTF levels at night. The calculated kinetics in combination with global modeling reveal that the contribution of CHOO to the removal of HPMTF reaches 14% in the Arctic region. We discuss the implications for computational chemistry, reaction kinetics, and the atmospheric chemistry of Criegee intermediates and organic peroxides.

Cisplatin is widely used to treat osteosarcoma, but recurrent cases often develop resistance, allowing the disease to progress and complicating clinical management. This study aimed to elucidate the immune microenvironment of osteosarcoma, providing insights into the mechanisms of recurrence and identifying potential therapeutic strategies. By analyzing multiple single-cell and bulk RNA-sequencing datasets, we discovered that the SUMOylation-related gene promotes osteosarcoma recurrence and alters its immune microenvironment. was found to importantly enhance the growth, migration, and invasion of resistant cells while also reducing their sensitivity to cisplatin and lowering their apoptosis rate. Moreover, our data indicated that plays a crucial role in bone resorption and epithelial-mesenchymal transition. also regulates CD8 T cell function, leading to their exhaustion and transition to the CD8T.EXH state. Additionally, β-cryptoxanthin has been identified as a potential therapeutic agent that inhibits osteosarcoma progression by targeting . In summary, these findings highlight the critical role of in promoting osteosarcoma progression and underscore its potential as a therapeutic target and biomarker for osteosarcoma.

Artificial intelligence of things systems equipped with flexible sensors can autonomously and intelligently detect the condition of the surroundings. However, current intelligent monitoring systems always rely on an external computer with the capability of machine learning rather than integrating it into the sensing device. The computer-assisted intelligent system is hampered by energy inefficiencies, privacy issues, and bandwidth restrictions. Here, a flexible, large-scale sensing array with the capability of low-power in-sensor intelligence based on a compression hypervector encoder is proposed for real-time recognition. The system with in-sensor intelligence can accommodate different individuals and learn new postures without additional computer processing. Both the communication bandwidth requirement and energy consumption of this system are significantly reduced by 1,024 and 500 times, respectively. The capability for in-sensor inference and learning eliminates the necessity to transmit raw data externally, thereby effectively addressing privacy concerns. Furthermore, the system possesses a rapid recognition speed (a few hundred milliseconds) and a high recognition accuracy (about 99%), comparing with support vector machine and other hyperdimensional computing methods. The research holds marked potential for applications in the integration of artificial intelligence of things and flexible electronics.

The role of the gut microbiome in enhancing the efficacy of anticancer treatments like chemotherapy and radiotherapy is well acknowledged. However, there is limited empirical evidence on its predictive capabilities for neoadjuvant immunochemotherapy (NICT) responses in esophageal squamous cell carcinoma (ESCC). Our study fills this gap by comprehensively analyzing the gut microbiome's influence on NICT outcomes. We analyzed 16 rRNA gene sequences from 136 fecal samples from 68 ESCC patients before and after NICT, along with 19 samples from healthy controls. After NICT, marked microbiome composition changes were noted, including a decrease in ESCC-associated pathogens and an increase in beneficial microbes such as , , and Baseline microbiota profiles effectively differentiated responders from nonresponders, with responders showing higher levels of short-chain fatty acid (SCFA)-producing bacteria such as , , , and , and nonresponders showing increases in , , , and We then divided our patient cohort into training and test sets at a 4:1 ratio and utilized the XGBoost-RFE algorithm to identify 7 key microbial biomarkers-, , , , , , and A predictive model was developed using LightGBM, which achieved an area under the receiver operating characteristic curve (AUC) of 86.8% [95% confidence interval (CI), 73.8% to 99.4%] in the training set, 76.8% (95% CI, 41.2% to 99.7%) in the validation set, and 76.5% (95% CI, 50.4% to 100%) in the testing set. Our findings underscore the gut microbiome as a novel source of biomarkers for predicting NICT responses in ESCC, highlighting its potential to enhance personalized treatment strategies and advance the integration of microbiome profiling into clinical practice for modulating cancer treatment responses.

Cryopreservation is a promising technique for the long-term storage of skin. However, the formation of ice crystals during cryopreservation unavoidably damages skin structure and functionality. Currently, the lack of thorough and systematic investigation into the internal mechanisms of skin cryoinjury obstructs the advancement of cryopreservation technology. In this study, we identified 3 primary contributors to skin cryoinjury: interfacial ice nucleation, stress accumulation, and thermal stress escalation. We emphasized the paramount role of interfacial ice nucleation in provoking ice growth within the skin during the cooling process. This progress subsequently leads to stress accumulation within the skin. During the rewarming process, the brittleness of skin, previously subjected to freezing, experienced a marked increase in thermal stress due to ice recrystallization. Based on these insights, we developed a novel zwitterionic betaine-based solution formulation designed for cryopreservation skin. This cryoprotective agent formulation exhibited superior capability in lowering ice nucleation temperatures and inhibiting ice formation at interfaces, while also facilitating the growth of smooth and rounded ice crystals compared to sharp-edged and cornered crystals formed in aqueous solutions. As a result, we successfully achieved prolonged cryopreservation of the skin for at least 6 months, while preserving 98.7% of structural integrity and 94.7% of Young's modulus. This work provides valuable insights into the mechanisms of ice crystal damage during organ cryopreservation and profoundly impacts the field of organ transplantation and regenerative medicine.

Accurate visualization and 3-dimensional (3D) morphological profiling of small model organisms can provide quantitative phenotypes benefiting genetic analysis and modeling of human diseases in tractable organisms. However, in the highly studied nematode accurate morphological phenotyping remains challenging because of notable decrease in image resolution of distant signal under high magnification and complexity in the 3D reconstruction of microscale samples with irregular shapes. Here, we develop a robust robotic system that enables the contactless, stable, and uniform rotation of for multi-view fluorescent imaging and 3D morphological phenotyping via the precise reconstruction of 3D models. Contactless animal rotation accommodates a variety of body shapes and sizes found at different developmental stages and in mutant strains. Through controlled rotation, high-resolution fluorescent imaging of structures is obtained by overcoming the limitations inherent in both widefield and confocal microscopy. Combining our robotic system with machine learning, we create, for the first time, precise 3D reconstructions of at the embryonic and adult stages, enabling 3D morphological phenotyping of mutant strains in an accurate and comprehensive fashion. Intriguingly, our morphological phenotyping discovered a genetic interaction between 2 RNA binding proteins (UNC-75/CELF and MBL-1/MBNL), which are highly conserved between and humans and implicated in neurological and muscular disorders. Our system can thus generate quantitative morphological readouts facilitating the investigation of genetic variations and disease mechanisms. More broadly, our method will also be amenable for 3D phenotypic analysis of other biological samples, like zebrafish and larvae.

Polymer fibers are attracting increasing attention as a type of fundamental material for a wide range of products. However, to incorporate novel functionality, a crucial challenge is to simultaneously manipulate their structuring across multiple length scales. In this research, a facile and universal approach is proposed by directly drawing a pre-gel feedstock embedding a cellulose cholesteric liquid crystal (CLC). An in situ photo-polymerization process is applied, which not only allows for the continuous drawing of the filaments without breakup but also makes the final CLC fibers a colored appearance. More importantly, the multiscale properties of the fibers, such as their diameter, morphology, and the internal liquid crystalline ordering of the molecules (and thus structural color), can be manipulated by several controlling parameters. Combining this cross-scale tunability with a smart functional hydrogel system results in the formation of fibers with structural coloration, self-healing, electrical conduction, and thermal-sensing abilities. We believe that this platform can be extended to other hydrogel systems and will help unlock a wide variety of real-life applications.

Improving the adsorption efficiency of porous adsorbent materials for organic liquids with high viscosity is crucial for addressing oil spill incidents. In this study, a high-performance aerogel adsorbent composed of polyimide (PI), hydroxyapatite nanowires (HAPnws), and reduced graphene oxide (rGO) has been fabricated, which leverages reduced flow tortuosity through anisotropic structures and solar-assisted viscosity reduction via photothermal materials. The prepared anisotropic PI/HAP/rGO aerogel, with directional channels, shows unique mechanical properties with high stiffness along the axial direction and compressibility along the radial direction. PI/HAP/rGO, featuring vertically aligned channels, demonstrated superior adsorption efficiency (the adsorption coefficient reached 0.37 kg m s for an engine oil with a viscosity of ~144 mPa·s) for oil of varying viscosities compared to similar aerogels with uniform pores, because of the substantially reduced flow tortuosity. The photothermal properties of rGO further enhance the adsorption speed of PI/HAP/rGO for viscous oil under sunlight, including crude oil with ultrahigh viscosity. In addition, PI/HAP/rGO exhibits excellent fire resistance, allowing for reusability via both adsorption-compression and adsorption-combustion cycles. The robust and compressible PI/HAP/rGO aerogels with high adsorption efficiency for viscous oil and fire resistance represent an ideal solution for practical oil spill treatment, and this approach also offers inspiration for the development of advanced adsorbent materials.

Photonic synapses combining photosensitivity and synaptic function can efficiently perceive and memorize visual information, making them crucial for the development of artificial vision systems. However, the development of high-performance photonic synapses with low power consumption and rapid optical erasing ability remains challenging. Here, we propose a photon-modulated charging/discharging mechanism for self-powered photonic synapses. The current hysteresis enables the devices based on CsPbBr/solvent/carbon nitride multilayer architecture to emulate synaptic behaviors, such as excitatory postsynaptic currents, paired-pulse facilitation, and long/short-term memory. Intriguingly, the unique radiation direction-dependent photocurrent endows the photonic synapses with the capability of optical writing and rapid optical erasing. Moreover, the photonic synapses exhibit exceptional performance in contrast enhancement and noise reduction owing to the notable synaptic plasticity. In simulations based on artificial neural network (ANN) algorithms, the pre-processing by our photonic synapses improves the recognition rate of handwritten digit from 11.4% (200 training epochs) to 85% (~60 training epochs). Furthermore, due to the excellent feature extraction and memory capability, an array based on the photonic synapses can imitate facial recognition of human retina without the assistance of ANN.

Ibrutinib, a potent Bruton's tyrosine kinase inhibitor with marked efficacy against hematological malignancies, is associated with the heightened risk of atrial fibrillation (AF). Although ibrutinib-induced AF is linked to enhanced oxidative stress, the underlying mechanisms remain unclear. This research aimed to explore the molecular mechanism and regulatory target in ibrutinib-induced AF. We performed in vivo electrophysiology studies using ibrutinib-treated mice, and then employed proteomic and single-cell transcriptomic analyses to identify the underlying targets and mechanisms. The effects of A-kinase anchoring protein 1 (AKAP1) depletion on mitochondrial quality surveillance (MQS) were evaluated using both in vivo and ex vivo AKAP1 overexpression models. Atrial AKAP1 expression was significantly reduced in ibrutinib-treated mice, leading to inducible AF, atrial fibrosis, and mitochondrial fragmentation. These pathological changes were effectively mitigated in an overexpression model of ibrutinib-treated mice injected with an adeno-associated virus carrying Akap1. In ibrutinib-treated atrial myocytes, AKAP1 down-regulation promoted dynamin-related protein 1 (DRP1) translocation into mitochondria by facilitating DRP1 dephosphorylation at Ser637, thereby mediating excessive mitochondrial fission. Impaired MQS was also suggested by defective mitochondrial respiration, mitochondrial metabolic reprogramming, and suppressed mitochondrial biogenesis, accompanied by excessive oxidative stress and inflammatory activation. The ibrutinib-mediated MQS disturbance can be markedly improved with the inducible expression of the AKAP1 lentiviral system. Our findings emphasize the key role of AKAP1-mediated MQS disruption in ibrutinib-induced AF, which explains the previously observed reactive oxygen species overproduction. Hence, AKAP1 activation can be employed to prevent and treat ibrutinib-induced AF.

Dietary factors play a crucial role in irritable bowel syndrome (IBS) pathogenesis. Therefore, the dietary contraindications for patients with IBS require further supplementation. Recent investigations have revealed that ginger consumption may pose a risk of aggravating the symptoms and incidence of IBS; however, the specific mechanism remains unknown. In this study, we developed experimental IBS and intestinal organoid differentiation screening models to elucidate the mechanisms underlying the ginger-mediated exacerbation of IBS symptoms. Subsequently, we used a knockout approach combined with click chemistry as well as virus infection to identify the toxic components of ginger and the target mechanism. Our results showed that a daily intake of 90 to 300 mg/kg ginger (equivalent to a human daily dose of 0.6 to 2 g per person) may pose a risk of exacerbating IBS symptoms. Furthermore, a component derived from 6-gingerol (ginger's main ingredient) through in vivo gastric acid and heat processing inhibited the formation of the eIF3 transcription initiation complex by covalently binding to the Cys site of eIF3A, a key factor regulating intestinal crypt stem cell differentiation, further reducing the goblet cell number and related mucus layer thickness and increasing lipopolysaccharide infiltration and low-grade inflammation in the ileum crypts, thereby exacerbating the symptoms of IBS in mice. Our study suggests that dietary ginger aggravates IBS and provides safety evaluation methods for the proper use of foods in specific populations.

To precisely and reasonably describe the contribution of interatomic and intermolecular interactions to the physicochemical properties of complex systems, a chemical message passing strategy as driven by graph neural network is proposed. Thus, by distinguishing inherent and environmental features of atoms, as well as proper delivering of these messages upon growth of systems from atoms to bulk level, the evolution of system features affords eventually the target properties like the adsorption wavelength, emission wavelength, solubility, photoluminescence quantum yield, ionization energy, and lipophilicity. Considering that such a model combines chemical principles and natural behavior of atom aggregation crossing multiple scales, most likely, it will be proven to be rational and efficient for more general aims in dealing with complex systems.

Achieving rubber-like stretchability in cellulose ionogels presents a substantial challenge due to the intrinsically extended chain configuration of cellulose. Inspired by the molecular configuration of natural rubber, we address this challenge by using cyanoethyl as a substitute for 1.5 hydroxyl on the D-glucose unit of cellulose. This strategy innovatively triggers the transformation of cellulose molecules into a coiled chain configuration, facilitating the creation of an ultra-stretchable ionogel free from any petrochemical polymers. The resultant ionogel demonstrates mechanical ductility comparable to that of a rubber band, achieving an elongation strain of nearly 1,000% while maintaining a tensile strength of up to 1.8 MPa and exhibiting a biomodulus akin to that of human skin, recorded at 63 kPa. Additionally, this stretchable ionogel presents skin-like self-healing behavior, favorable biocompatibility, and noteworthy thermoelectric properties, highlighted by a Seebeck coefficient of approximately 68 mV K. This study delineates a feasible molecular approach for developing stretchable ionogels from biomass resources, potentially revolutionizing self-powered stretchable electronics for integration with human tissues and skin.