Lithium carbonate revitalizes tumor-reactive CD8+ T cells by shunting lactic acid into mitochondria.

The steady flow of lactic acid (LA) from tumor cells to the extracellular space via the monocarboxylate transporter symport system suppresses antitumor T cell immunity. However, LA is a natural energy metabolite that can be oxidized in the mitochondria and could potentially stimulate T cells. Here we show that the lactate-lowering mood stabilizer lithium carbonate (LC) can inhibit LA-mediated CD8+ T cell immunosuppression. Cytoplasmic LA increased the pumping of protons into lysosomes. LC interfered with vacuolar ATPase to block lysosomal acidification and rescue lysosomal diacylglycerol-PKCθ signaling to facilitate monocarboxylate transporter 1 localization to mitochondrial membranes, thus transporting LA into the mitochondria as an energy source for CD8+ T cells. These findings indicate that targeting LA metabolism using LC could support cancer immunotherapy.

Wavefunction matching for solving quantum many-body problems.

Ab initio calculations have an essential role in our fundamental understanding of quantum many-body systems across many subfields, from strongly correlated fermions1-3 to quantum chemistry4-6 and from atomic and molecular systems7-9 to nuclear physics10-14. One of the primary challenges is to perform accurate calculations for systems where the interactions may be complicated and difficult for the chosen computational method to handle. Here we address the problem by introducing an approach called wavefunction matching. Wavefunction matching transforms the interaction between particles so that the wavefunctions up to some finite range match that of an easily computable interaction. This allows for calculations of systems that would otherwise be impossible owing to problems such as Monte Carlo sign cancellations. We apply the method to lattice Monte Carlo simulations15,16 of light nuclei, medium-mass nuclei, neutron matter and nuclear matter. We use high-fidelity chiral effective field theory interactions17,18 and find good agreement with empirical data. These results are accompanied by insights on the nuclear interactions that may help to resolve long-standing challenges in accurately reproducing nuclear binding energies, charge radii and nuclear-matter saturation in ab initio calculations19,20.

Single-particle rotational microrheology enables pathological staging of macrophage foaming and antiatherosclerotic studies.

The formation of macrophage-derived foam cells has been recognized as the pathological hallmark of atherosclerotic diseases. However, the pathological evolution dynamics and underlying regulatory mechanisms remain largely unknown. Herein, we introduce a single-particle rotational microrheology method for pathological staging of macrophage foaming and antiatherosclerotic explorations by probing the dynamic changes of lysosomal viscous feature over the pathological evolution progression. The principle of this method involves continuous monitoring of out-of-plane rotation-caused scattering brightness fluctuations of the gold nanorod (AuNR) probe-based microrheometer and subsequent determination of rotational relaxation time to analyze the viscous feature in macrophage lysosomes. With this method, we demonstrated the lysosomal viscous feature as a robust pathological reporter and uncovered three distinct pathological stages underlying the evolution dynamics, which are highly correlated with a pathological stage-dependent activation of the NLRP3 inflammasome-involved positive feedback loop. We also validated the potential of this positive feedback loop as a promising therapeutic target and revealed the time window-dependent efficacy of NLRP3 inflammasome-targeted drugs against atherosclerotic diseases. To our knowledge, the pathological staging of macrophage foaming and the pathological stage-dependent activation of the NLRP3 inflammasome-involved positive feedback mechanism have not yet been reported. These findings provide insights into in-depth understanding of evolutionary features and regulatory mechanisms of macrophage foaming, which can benefit the analysis of effective therapeutical drugs as well as the time window of drug treatment against atherosclerotic diseases in preclinical studies.

ARL6IP1 mediates small-molecule-induced alleviation of Alzheimer pathology through FXR1-dependent BACE1 translation initiation.

Exploring the potential lead compounds for Alzheimer's disease (AD) remains one of the challenging tasks. Here, we report that the plant extract conophylline (CNP) impeded amyloidogenesis by preferentially inhibiting BACE1 translation via the 5' untranslated region (5'UTR) and rescued cognitive decline in an animal model of APP/PS1 mice. ADP-ribosylation factor-like protein 6-interacting protein 1 (ARL6IP1) was then found to mediate the effect of CNP on BACE1 translation, amyloidogenesis, glial activation, and cognitive function. Through analysis of the 5'UTR-targetd RNA-binding proteins by RNA pulldown combined with LC-MS/MS, we found that FMR1 autosomal homolog 1 (FXR1) interacted with ARL6IP1 and mediated CNP-induced reduction of BACE1 by regulating the 5'UTR activity. Without altering the protein levels of ARL6IP1 and FXR1, CNP treatment promoted ARL6IP1 interaction with FXR1 and inhibited FXR1 binding to the 5'UTR both in vitro and in vivo. Collectively, CNP exhibited a therapeutic potential for AD via ARL6IP1. Through pharmacological manipulation, we uncovered a dynamic interaction between FXR1 and the 5'UTR in translational control of BACE1, adding to the understanding of the pathophysiology of AD.

24-Hour Urinary Sodium and Potassium Excretion and Cardiovascular Risk.

BACKGROUND: The relation between sodium intake and cardiovascular disease remains controversial, owing in part to inaccurate assessment of sodium intake. Assessing 24-hour urinary excretion over a period of multiple days is considered to be an accurate method. METHODS: We included individual-participant data from six prospective cohorts of generally healthy adults; sodium and potassium excretion was assessed with the use of at least two 24-hour urine samples per participant. The primary outcome was a cardiovascular event (coronary revascularization or fatal or nonfatal myocardial infarction or stroke). We analyzed each cohort using consistent methods and combined the results using a random-effects meta-analysis. RESULTS: Among 10,709 participants, who had a mean (±SD) age of 51.5±12.6 years and of whom 54.2% were women, 571 cardiovascular events were ascertained during a median study follow-up of 8.8 years (incidence rate, 5.9 per 1000 person-years). The median 24-hour urinary sodium excretion was 3270 mg (10th to 90th percentile, 2099 to 4899). Higher sodium excretion, lower potassium excretion, and a higher sodium-to-potassium ratio were all associated with a higher cardiovascular risk in analyses that were controlled for confounding factors (P≤0.005 for all comparisons). In analyses that compared quartile 4 of the urinary biomarker (highest) with quartile 1 (lowest), the hazard ratios were 1.60 (95% confidence interval [CI], 1.19 to 2.14) for sodium excretion, 0.69 (95% CI, 0.51 to 0.91) for potassium excretion, and 1.62 (95% CI, 1.25 to 2.10) for the sodium-to-potassium ratio. Each daily increment of 1000 mg in sodium excretion was associated with an 18% increase in cardiovascular risk (hazard ratio, 1.18; 95% CI, 1.08 to 1.29), and each daily increment of 1000 mg in potassium excretion was associated with an 18% decrease in risk (hazard ratio, 0.82; 95% CI, 0.72 to 0.94). CONCLUSIONS: Higher sodium and lower potassium intakes, as measured in multiple 24-hour urine samples, were associated in a dose-response manner with a higher cardiovascular risk. These findings may support reducing sodium intake and increasing potassium intake from current levels. (Funded by the American Heart Association and the National Institutes of Health.).

Designing antimicrobial peptides using deep learning and molecular dynamic simulations.

With the emergence of multidrug-resistant bacteria, antimicrobial peptides (AMPs) offer promising options for replacing traditional antibiotics to treat bacterial infections, but discovering and designing AMPs using traditional methods is a time-consuming and costly process. Deep learning has been applied to the de novo design of AMPs and address AMP classification with high efficiency. In this study, several natural language processing models were combined to design and identify AMPs, i.e. sequence generative adversarial nets, bidirectional encoder representations from transformers and multilayer perceptron. Then, six candidate AMPs were screened by AlphaFold2 structure prediction and molecular dynamic simulations. These peptides show low homology with known AMPs and belong to a novel class of AMPs. After initial bioactivity testing, one of the peptides, A-222, showed inhibition against gram-positive and gram-negative bacteria. The structural analysis of this novel peptide A-222 obtained by nuclear magnetic resonance confirmed the presence of an alpha-helix, which was consistent with the results predicted by AlphaFold2. We then performed a structure-activity relationship study to design a new series of peptide analogs and found that the activities of these analogs could be increased by 4-8-fold against Stenotrophomonas maltophilia WH 006 and Pseudomonas aeruginosa PAO1. Overall, deep learning shows great potential in accelerating the discovery of novel AMPs and holds promise as an important tool for developing novel AMPs.

Hnrnpk protects against osteoarthritis through targeting WWC1 mRNA and inhibiting Hippo signaling pathway.

Osteoarthritis (OA) is an age-related or post-traumatic degenerative whole joint disease characterized by the rupture of articular cartilage homeostasis, the regulatory mechanisms of which remain elusive. This study identifies the essential role of heterogeneous nuclear ribonucleoprotein K (hnRNPK) in maintaining articular cartilage homeostasis. Hnrnpk expression is markedly downregulated in human and mice OA cartilage. The deletion of Hnrnpk effectively accelerates the development of post-traumatic and age-dependent OA in mice. Mechanistically, the KH1 and KH2 domain of Hnrnpk bind and degrade the mRNA of WWC1. Hnrnpk deletion increases WWC1 expression, which in turn leads to the activation of Hippo signaling and ultimately aggravates OA. In particular, intra-articular injection of LPA and adeno-associated virus serotype 5 expressing WWC1 RNA interference ameliorates cartilage degeneration induced by Hnrnpk deletion, and intra-articular injection of adeno-associated virus serotype 5 expressing Hnrnpk protects against OA. Collectively, this study reveals the critical roles of Hnrnpk in inhibiting OA development through WWC1-dependent downregulation of Hippo signaling in chondrocytes and defines a potential target for the prevention and treatment of OA.

YLC-assembly: large DNA assembly via yeast life cycle.

As an enabling technique of synthetic biology, the scale of DNA assembly largely determines the scale of genetic manipulation. However, large DNA assembly technologies are generally cumbersome and inefficient. Here, we developed a YLC (yeast life cycle)-assembly method that enables in vivo iterative assembly of large DNA by nesting cell-cell transfer of assembled DNA in the cycle of yeast mating and sporulation. Using this method, we successfully assembled a hundred-kilobase (kb)-sized endogenous yeast DNA and a megabase (Mb)-sized exogenous DNA. For each round, over 104 positive colonies per 107 cells could be obtained, with an accuracy ranging from 67% to 100%. Compared with other Mb-sized DNA assembly methods, this method exhibits a higher success rate with an easy-to-operate workflow that avoid in vitro operations of large DNA. YLC-assembly lowers the technical difficulty of Mb-sized DNA assembly and could be a valuable tool for large-scale genome engineering and synthetic genomics.

A flexible and highly sensitive organic electrochemical transistor-based biosensor for continuous and wireless nitric oxide detection.

As nitric oxide (NO) plays significant roles in a variety of physiological processes, the capability for real-time and accurate detection of NO in live organisms is in great demand. Traditional assessments of NO rely on indirect colorimetric techniques or electrochemical sensors that often comprise rigid constituent materials and can hardly satisfy sensitivity and spatial resolution simultaneously. Here, we report a flexible and highly sensitive biosensor based on organic electrochemical transistors (OECTs) capable of continuous and wireless detection of NO in biological systems. By modifying the geometry of the active channel and the gate electrodes of OECTs, devices achieve optimum signal amplification of NO. The sensor exhibits a low response limit, a wide linear range, high sensitivity, and excellent selectivity, with a miniaturized active sensing region compared with a conventional electrochemical sensor. The device demonstrates continuous detection of the nanomolar range of NO in cultured cells for hours without significant signal drift. Real-time and wireless measurement of NO is accomplished for 8 d in the articular cavity of New Zealand White rabbits with anterior cruciate ligament (ACL) rupture injuries. The observed high level of NO is associated with the onset of osteoarthritis (OA) at the later stage. The proposed device platform could provide critical information for the early diagnosis of chronic diseases and timely medical intervention to optimize therapeutic efficacy.

Rapid Fabrication of High-Resolution Flexible Electronics via Nanoparticle Self-Assembly and Transfer Printing.

Printed electronic technology serves as a key component in flexible electronics and wearable devices, yet achieving compatibility with both high resolution and high efficiency remains a significant challenge. Here, we propose a rapid fabrication method of high-resolution nanoparticle microelectronics via self-assembly and transfer printing. The tension gradient-electrostatic attraction composite-induced nanoparticle self-assembly strategy is constructed, which can significantly enhance the self-assembly efficiency, stability, and coverage by leveraging the meniscus Marangoni effect and the electric double-layer effect. The close-packed nanoparticle self-assembly layer can be rapidly formed on microstructure surfaces over a large area. Inspired by ink printing, a transfer printing strategy is further proposed to transform the self-assembly layer into conformal micropatterns. Large-area, high-resolution (2 µm), and ultrathin (1 µm) nanoparticle microelectronics can be stably fabricated, yielding a significant improvement over fluid printing methods. The unique deformability, recoverability, and scalability of nanoparticle microelectronics are revealed, providing promising opportunities for various academic and real applications.