Regulatory role of Mycobacterium tuberculosis MtrA on dormancy/resuscitation revealed by a novel target gene-mining strategy.

Introduction: The unique dormancy of Mycobacterium tuberculosis plays a significant role in the major clinical treatment challenge of tuberculosis, such as its long treatment cycle, antibiotic resistance, immune escape, and high latent infection rate. Methods: To determine the function of MtrA, the only essential response regulator, one strategy was developed to establish its regulatory network according to high-quality genome-wide binding sites. Results and discussion: The complex modulation mechanisms were implied by the strong bias distribution of MtrA binding sites in the noncoding regions, and 32.7% of the binding sites were located inside the target genes. The functions of 288 potential MtrA target genes predicted according to 294 confirmed binding sites were highly diverse, and DNA replication and damage repair, lipid metabolism, cell wall component biosynthesis, cell wall assembly, and cell division were the predominant pathways. Among the 53 pathways shared between dormancy/resuscitation and persistence, which accounted for 81.5% and 93.0% of the total number of pathways, respectively, MtrA regulatory genes were identified not only in 73.6% of their mutual pathways, but also in 75.4% of the pathways related to dormancy/resuscitation and persistence respectively. These results suggested the pivotal roles of MtrA in regulating dormancy/resuscitation and the apparent relationship between dormancy/resuscitation and persistence. Furthermore, the finding that 32.6% of the MtrA regulons were essential in vivo and/or in vitro for M. tuberculosis provided new insight into its indispensability. The findings mentioned above indicated that MtrA is a novel promising therapeutic target for tuberculosis treatment since the crucial function of MtrA may be a point of weakness for M. tuberculosis.

Cockayne Syndrome Linked to Elevated R-Loops Induced by Stalled RNA Polymerase II during Transcription Elongation.

Mutations in the Cockayne Syndrome group B (CSB) gene cause cancer in mice, but premature aging and severe neurodevelopmental defects in humans. CSB, a member of the SWI/SNF family of chromatin remodelers, plays diverse roles in regulating gene expression and transcription-coupled nucleotide excision repair (TC-NER); however, these functions do not explain the distinct phenotypic differences observed between CSB-deficient mice and humans. During investigating Cockayne Syndrome-associated genome instability, we uncover an intrinsic mechanism that involves elongating RNA polymerase II (RNAPII) undergoing transient pauses at internal T-runs where CSB is required to propel RNAPII forward. Consequently, CSB deficiency retards RNAPII elongation in these regions, and when coupled with G-rich sequences upstream, exacerbates genome instability by promoting R-loop formation. These R-loop prone motifs are notably abundant in relatively long genes related to neuronal functions in the human genome, but less prevalent in the mouse genome. These findings provide mechanistic insights into differential impacts of CSB deficiency on mice versus humans and suggest that the manifestation of the Cockayne Syndrome phenotype in humans results from the progressive evolution of mammalian genomes.

Development of an Orally Bioavailable LCK PROTAC Degrader as a Potential Therapeutic Approach to T-Cell Acute Lymphoblastic Leukemia.

Despite significant advances over recent years, the treatment of T cell acute lymphoblastic leukemia (T-ALL) remains challenging. We have recently shown that a subset of T-ALL cases exhibited constitutive activation of the lymphocyte-specific protein tyrosine kinase (LCK) and were consequently responsive to treatments with LCK inhibitors and degraders such as dasatinib and dasatinib-based PROTACs. Here we report the design, synthesis and in vitro/vivo evaluation of SJ45566, a potent and orally bioavailable LCK PROTAC.

Virtual node graph neural network for full phonon prediction.

Understanding the structure-property relationship is crucial for designing materials with desired properties. The past few years have witnessed remarkable progress in machine-learning methods for this connection. However, substantial challenges remain, including the generalizability of models and prediction of properties with materials-dependent output dimensions. Here we present the virtual node graph neural network to address the challenges. By developing three virtual node approaches, we achieve Γ-phonon spectra and full phonon dispersion prediction from atomic coordinates. We show that, compared with the machine-learning interatomic potentials, our approach achieves orders-of-magnitude-higher efficiency with comparable to better accuracy. This allows us to generate databases for Γ-phonon containing over 146,000 materials and phonon band structures of zeolites. Our work provides an avenue for rapid and high-quality prediction of phonon band structures enabling materials design with desired phonon properties. The virtual node method also provides a generic method for machine-learning design with a high level of flexibility.

Hierarchical supramolecules composed of starch-based nanocluster aggregates with light-responsive mechanical strain for remotely rapid and precise actuation.

Hierarchical supramolecular systems, characterized by nanoscale sensitivity and macroscopic tangible changes, offer promising perspectives for the design of remotely controllable, rapid, and precise actuation materials, serving as a potential substitution for non-intelligent and complex actuation switches. Herein, we reported on the disassembly of orderly and rigid starch helical covalent structures, and their subsequent reassembly into a hierarchical supramolecular gel composed of nanocluster aggregates, integrating supramolecular interactions of three different scales. The incorporation of photo-sensitive FeIIITA, a complex of trivalent iron ions and tannic acid, significantly enhances the photo-responsive strain capacity of the hierarchical supramolecular gel. The supramolecular gel exhibits its features in a rapid light-responsive rate of hardness and viscosity, enabling the actuation of objects within 22 s under light exposure when employed as a remote actuation switch. Meanwhile, this actuation mechanism of the hierarchical supramolecular gel also has a promising perspective in precise control, identifying and actuating one of the two objects in distances of 0.8 mm even smaller scales. Our work provides a reliable reference for replacing complex actuation switches with intelligent materials for remote, rapid, and accurate actuation, and offers valuable insights for actuation in harsh and vacuum outdoor environments.

Reversal of gentamicin sulfate resistance in avian pathogenic Escherichia coli by matrine combined with berberine hydrochloride.

In recent years, the evolution of antibiotic resistance has led to the inefficacy of several antibiotics, and the reverse of resistance was a novel method to solve this problem. We previously demonstrated that matrine (Mat) and berberine hydrochloride (Ber) had a synergistic effect against multidrug-resistant Escherichia coli (MDREC). This study aimed to demonstrate the effect of Mat combined with Ber in reversing the resistance of MDREC. The MDREC was sequenced passaged in the presence of Mat, Ber, and a combination of Mat and Ber, which did not affect its growth. The reverse rate was up to 39.67% after MDREC exposed to Mat + Ber for 15 days. The strain that reversed resistance was named drug resistance reversed E. coli (DRREC) and its resistance to ampicillin, streptomycin, gentamicin, and tetracycline was reversed. The MIC of Gentamicin Sulfate (GS) against DRREC decreased 128-fold to 0.63 µg/mL, and it was stable within 20 generations. Furthermore, the susceptible phenotype of DRREC remained stable within 20 generations, as well. The LD50 of DRREC for chickens was 8.69 × 109 CFU/mL. qRT-PCR assays revealed that the transcript levels of antibiotic-resistant genes and virulence genes in the DRREC strain were significantly lower than that in the MDREC strain (P < 0.05). In addition, GS decreased the death, decreased the bacterial loading in organs, alleviated the injury of the spleen and liver, and decreased the cytokine levels in the chickens infected by the DRREC strain. In contrast, the therapeutic effect of GS in chickens infected with MDREC was not as evident. These findings suggest that the combination of Mat and Ber has potential for reversing resistance to MDREC.

Chinese herbal medicine Shufeng Jiedu capsule for mild to moderate COVID-19: a multicenter, randomized, double-blind, placebo-controlled phase II trial.

Background: The COVID-19 pandemic has had a profound global impact, although the majority of recently infected cases have presented with mild to moderate symptoms. Previous clinical studies have demonstrated that Shufeng Jiedu (SFJD) capsule, a Chinese herbal patent medicine, effectively alleviates symptoms associated with the common cold, H1N1 influenza, and COVID-19. This study aimed to assess the efficacy and safety of SFJD capsules in managing symptoms of mild to moderate COVID-19 infection. Methods: A randomized, double-blind, placebo-controlled trial was conducted from May to December 2022 at two hospitals in China. Mild and moderate COVID-19-infected patients presenting respiratory symptoms within 3 days from onset were randomly assigned to either the SFJD or placebo groups in a 1:1 ratio. Individuals received SFJD capsules or a placebo three times daily for five consecutive days. Participants were followed up for more than 14 days after their RT-PCR nucleoid acid test for SARS-CoV-2 turned negative. The primary outcome measure was time to alleviate COVID-19 symptoms from baseline until the end of follow-up. Results: A total of 478 participants were screened; ultimately, 407 completed the trial after randomization (SFJD, n = 203; placebo, n = 204). No statistically significant difference in baseline parameters was observed between the two groups. The median time to alleviate all symptoms was 7 days in the SFJD group compared to 8 days in the placebo group (p = 0.037). Notably, the SFJD group significantly attenuated fever/chills (p = 0.04) and headache (p = 0.016) compared to the placebo group. Furthermore, the median time taken to reach normal body temperature within 24 h was reduced by 7 hours in the SFJD group compared to the placebo group (p = 0.033). No deaths or instances of serious or critical conditions occurred during this trial period; moreover, no serious adverse events were reported. Conclusion: The trial was conducted in a unique controlled hospital setting, and the 5-day treatment with SFJD capsules resulted in a 1-day reduction in overall symptoms, particularly headache and fever/chills, among COVID-19-infected participants with mild or moderate symptoms. Compared to placebo, SFJD capsules were found to be safe with fewer side effects. SFJD capsules could potentially serve as an effective treatment for alleviating mild to moderate symptoms of COVID-19. Clinical Trial Registration: https://www.isrctn.com/, identifier ISRCTN14236594.

Nanorobot-based Direct Implantation of Flexible Neural Electrode for BCI.

Brain-Computer Interface (BCI) has gained remarkable prominence in biomedical community. While BCI holds vast potential across diverse domains, the implantation of neural electrodes poses multifaceted challenges to fully explore the power of BCI. Conventional rigid electrodes face the problem of foreign body reaction induced by mechanical mismatch to biological tissue, while flexible electrodes, though more preferential, lack controllability during implantation. Researchers have explored various strategies, from assistive shuttle to biodegradable coatings, to strike a balance between implantation rigidity and post-implantation flexibility. Yet, these approaches may introduce complications, including immune response, inflammations, and raising intracranial pressure. To this end, this paper proposes a novel nanorobot-based technique for direct implantation of flexible neural electrodes, leveraging the high controllability and repeatability of robotics to enhance the implantation quality. This approach features a dual-arm nanorobotic system equipped with stereo microscope, by which a flexible electrode is first visually aligned to the target neural tissue to establish contact and thereafter implanted into brain with well controlled insertion direction and depth. The key innovation is, through dual-arm coordination, the flexible electrode maintains straight along the implantation direction. With this approach, we implanted CNTf electrodes into cerebral cortex of mouse, and captured standard spiking neural signals.

Application of deep learning classification model for regional evaluation of roof pressure support evolution effects over time in coal mining face.

Hydraulic support leg pressure serves as a crucial indicator for assessing work face support quality. Current evaluation methods for support quality primarily concentrate on static analyses-like inadequate initial support force, pressure overrun, and uneven bracket force-while neglecting dynamic column pressure changes. This paper introduces a model for assessing hydraulic support quality using deep learning techniques. Real-time data is preprocessed into a spatio-temporal pressure sub-matrix sample, which is then inputted into the model. This process assesses the support quality type and characterizes its dynamic evolution within the area. The model facilitates the identification of dynamic support quality effects in the working face area, aiding operators in making targeted adjustments to hydraulic support status. Experimental results revealed that the optimized LeNet-5 network-adjusting parameters like convolutional layer count, kernel size, and ReLU activation function-achieved the highest classification accuracy of 85.25 % for support quality, surpassed other networks. Furthermore, the improved LeNet-5 network outperformed other networks in both F1 score and recall. Additionally, the improved LeNet-5 network achieved faster convergence to the optimal solution, accelerated training speed. This highlighted its advantages in evaluating the spatio-temporal support quality of hydraulic supports in smart mining operations.

TRANSPARENT TESTA GLABRA1 Regulates High-Intensity Blue Light-Induced Phototropism by Reducing CRYPTOCHROME1 Levels.

The asymmetrical distribution of auxin supports high intensity blue light (HBL)-mediated phototropism. Flavonoids, secondary metabolites induced by blue light and TRANSPARENT TESTA GLABRA1 (TTG1), alter auxin transport. However, the role of TTG1 in HBL-induced phototropism in Arabidopsis (Arabidopsis thaliana) remains unclear. We found that TTG1 regulates HBL-mediated phototropism. HBL-induced degradation of CRYPTOCHROME 1 (CRY1) was repressed in ttg1-1, and depletion of CRY1 rescued the phototropic defects of the ttg1-1 mutant. Moreover, overexpression of CRY1 in a cry1 mutant background led to phototropic defects in response to HBL. These results indicated that CRY1 is involved in the regulation of TTG1-mediated phototropism in response to HBL. Further investigation showed that TTG1 physically interacts with CRY1 via its N-terminus and that the added TTG1 promotes the dimerization of CRY1. The interaction between TTG1 and CRY1 may promote HBL-mediated degradation of CRY1. TTG1 also physically interacted with blue light inhibitor of cryptochrome 1 (BIC1) and Light-Response Bric-a-Brack/Tramtrack/Broad 2 (LRB2), and these interactions either inhibited or promoted their interaction with CRY1. Exogenous gibberellins (GA) and auxins, two key plant hormones that crosstalk with CRY1, may confer the recovery of phototropic defects in the ttg1-1 mutant and CRY1-overexpressing plants. Our results revealed that TTG1 participates in the regulation of HBL-induced phototropism by modulating CRY1 levels, which are coordinated with GA or IAA signaling.

Study on coal pulverization characteristics and gas desorption mechanism based on impact crushing experiment.

The coal's particle size distribution properties after pulverization and the gas desorption behavior driven by pulverization are of profound meaning to the study of coal and gas outburst mechanism. In this paper, based on the impact crushing experiment, the tectonic coal and primary coal are crushed under different impact energy conditions. After screening the broken coal, the particle size distribution law is analyzed, and the characterization function suitable for the particle size distribution of coal particles after crushing is determined. The relationship between crushing work and new surface area and fractal dimension of coal body is discussed. The consequences indicated that the mass proportion of tectonic coal below 0.074 mm particle size is much huger than that of raw coal. G-S, R-R, and fractal distribution model describe the best particle size distribution of the two coals in the scope of 0.074∼4 mm. The new surface area added increases with the crushing work, and the tectonic coal is 1.34-1.96 times that of the raw coal. The fractal dimension diminishes first and then increases with the crushing work ratio. In addition, the gas desorption amount of coal particles with different particle sizes after coal pulverization was measured, and a dynamic model suitable for coal pulverization-driven gas desorption was established, and the experimental results were verified. The research results of this paper can provide experimental and theoretical basis for the analysis of energy dissipation in coal and gas outburst.

Reciprocal conversion between annual and polycarpic perennial flowering behavior in the Brassicaceae.

The development of perennial crops holds great promise for sustainable agriculture and food security. However, the evolution of the transition between perenniality and annuality is poorly understood. Here, using two Brassicaceae species, Crucihimalaya himalaica and Erysimum nevadense, as polycarpic perennial models, we reveal that the transition from polycarpic perennial to biennial and annual flowering behavior is a continuum determined by the dosage of three closely related MADS-box genes. Diversification of the expression patterns, functional strengths, and combinations of these genes endows species with the potential to adopt various life-history strategies. Remarkably, we find that a single gene among these three is sufficient to convert winter-annual or annual Brassicaceae plants into polycarpic perennial flowering plants. Our work delineates a genetic basis for the evolution of diverse life-history strategies in plants and lays the groundwork for the generation of diverse perennial Brassicaceae crops in the future.

Relationship between age and remimazolam dose required for inducing loss of consciousness in older surgical patients.

Background: Remimazolam is a new ultra-short-acting benzodiazepine for procedural sedation and general anaesthesia, characterised by rapid onset of action, quick recovery, and organ-independent metabolism. Older patients tend to sustain more treatment-emergent adverse events (TEAEs) and worse perioperative prognoses after receiving remimazolam. However, few studies have investigated the appropriate dose of remimazolam for loss of consciousness (LOC) in geriatric patients. We designed this study to provide evidence for dose references and elucidate the relationship between age and remimazolam requirement for inducing LOC during anaesthesia induction. Methods: Exactly 120 patients scheduled for general surgery under general anaesthesia were included and divided into two groups: Group A (60 patients, 18-64 years) and Group B (60 patients, ≥ 65 years). LOC, defined as a Modified Observer's Assessment of Alertness and Sedation score at 1 had been reached, emerged after all participants received a continuous infusion of remimazolam at a rate of 0.05 mg/kg/min. Results: The remimazolam required for inducing LOC was 0.26 and 0.19 mg/kg in groups A and B, respectively, and the remimazolam dose in group B decreased by 26.9% compared to group A. According to the bivariate linear correlation analysis, remimazolam requirement was negatively correlated with age. Multivariable linear regression models and further adjustments for potential impact factors indicated that age was an independent factor for the remimazolam dose required for LOC. Conclusion: This study demonstrated that age was significantly and independently correlated with the remimazolam requirement for inducing LOC. To obtain haemodynamic stability during the induction of general anaesthesia, appropriately reducing the remimazolam dose is recommended for geriatric patients.

PD-1/CD80+ small extracellular vesicles from immunocytes induce cold tumours featured with enhanced adaptive immunosuppression.

Only a minority of cancer patients benefit from immune checkpoint blockade therapy. Sophisticated cross-talk among different immune checkpoint pathways as well as interaction pattern of immune checkpoint molecules carried on circulating small extracellular vesicles (sEV) might contribute to the low response rate. Here we demonstrate that PD-1 and CD80 carried on immunocyte-derived sEVs (I-sEV) induce an adaptive redistribution of PD-L1 in tumour cells. The resulting decreased cell membrane PD-L1 expression and increased sEV PD-L1 secretion into the circulation contribute to systemic immunosuppression. PD-1/CD80+ I-sEVs also induce downregulation of adhesion- and antigen presentation-related molecules on tumour cells and impaired immune cell infiltration, thereby converting tumours to an immunologically cold phenotype. Moreover, synchronous analysis of multiple checkpoint molecules, including PD-1, CD80 and PD-L1, on circulating sEVs distinguishes clinical responders from those patients who poorly respond to anti-PD-1 treatment. Altogether, our study shows that sEVs carry multiple inhibitory immune checkpoints proteins, which form a potentially targetable adaptive loop to suppress antitumour immunity.

SEEI: spherical evolution with feedback mechanism for identifying epistatic interactions.

BACKGROUND: Detecting epistatic interactions (EIs) involves the exploration of associations among single nucleotide polymorphisms (SNPs) and complex diseases, which is an important task in genome-wide association studies. The EI detection problem is dependent on epistasis models and corresponding optimization methods. Although various models and methods have been proposed to detect EIs, identifying EIs efficiently and accurately is still a challenge. RESULTS: Here, we propose a linear mixed statistical epistasis model (LMSE) and a spherical evolution approach with a feedback mechanism (named SEEI). The LMSE model expands the existing single epistasis models such as LR-Score, K2-Score, Mutual information, and Gini index. The SEEI includes an adaptive spherical search strategy and population updating strategy, which ensures that the algorithm is not easily trapped in local optima. We analyzed the performances of 8 random disease models, 12 disease models with marginal effects, 30 disease models without marginal effects, and 10 high-order disease models. The 60 simulated disease models and a real breast cancer dataset were used to evaluate eight algorithms (SEEI, EACO, EpiACO, FDHEIW, MP-HS-DHSI, NHSA-DHSC, SNPHarvester, CSE). Three evaluation criteria (pow1, pow2, pow3), a T-test, and a Friedman test were used to compare the performances of these algorithms. The results show that the SEEI algorithm (order 1, averages ranks = 13.125) outperformed the other algorithms in detecting EIs. CONCLUSIONS: Here, we propose an LMSE model and an evolutionary computing method (SEEI) to solve the optimization problem of the LMSE model. The proposed method performed better than the other seven algorithms tested in its ability to identify EIs in genome-wide association datasets. We identified new SNP-SNP combinations in the real breast cancer dataset and verified the results. Our findings provide new insights for the diagnosis and treatment of breast cancer. AVAILABILITY AND IMPLEMENTATION: https://github.com/scutdy/SSO/blob/master/SEEI.zip .