Ginsenoside Rh2 suppresses ferroptosis in ulcerative colitis by targeting specific protein 1 by upregulating microRNA-125a-5p.

BACKGROUND: Worldwide, ulcerative colitis (UC) is becoming increasingly fast growing. Ginsenoside Rh2 has been reported to alleviate UC. However, the latent biological mechanism of Rh2 in the treatment of UC remains uncertain. In this study, the goal was to determine the therapeutic effect of Rh2 on dextran sulfate sodium (DSS)-induced UC. METHODS: A DSS-induced UC mouse model was established and divided into 7 groups for Rh2 gavage and/or miR-125a-5p lentivirus injection (n = 10 per group). Colonic specimens were collected for phenotypic and pathological analysis. miR-125a-5p and specific protein 1 (SP1) expression, inflammation-related factors IL-6 and IL-10, and apoptosis were detected in mice. Human normal colon epithelial cell line NCM460 was treated with H2O2 and ferric chloride hexahydrate to construct an in vitro cell model of colitis and induce ferroptosis. Independent sample t-test was used to compare cell proliferation, cell entry, apoptosis, and oxidative stress between the two groups. One way analysis of variance combined with the least significant difference t test was used for comparison between groups. Multiple time points were compared by repeated measurement analysis of variance. RESULTS: DSS-induced UC mice had significantly decreased body weight, increased disease activity index, decreased colon length, and decreased miR-125a-5p expression (all P < 0.05). In the DSS-induced mouse model, the expression of miR-125a-5p rebounded and ferroptosis was inhibited after Rh2 treatment (all P < 0.05). Inhibition of miR-125a-5p or upregulation of SP1 expression counteracted the protective effects of Rh2 on UC mice and ferroptosis cell models (all P < 0.05). CONCLUSIONS: Rh2 mitigated DSS-induced colitis in mice and restrained ferroptosis by targeting miR-125a-5p. Downregulating miR-125a-5p or elevating SP1 could counteract the protective impacts of Rh2 on ferroptotic cells. The findings convey that Rh2 has a latent application value in the treatment of UC.

Flexible Wearable Tri-notched UWB Antenna Printed with Silver Conductive Materials.

The advancement of Internet of Things and associated technologies has led to the widespread usage of smart wearable devices, greatly boosting the demand for flexible antennas, which are critical electromagnetic components in such devices. Additive manufacturing technologies provide a feasible solution for the creation of wearable and flexible antennas. However, performance reliability under deformation and radiation safety near the human body are two issues that need to be solved for such antennas. Currently, there are few reports on compact, flexible ultrawideband (UWB) antennas with more notch numbers, reliable bendability, and radiation safety. In this paper, a UWB antenna with trinotched characteristics for wearable applications was proposed and developed using printable conductive silver materials consisting of silver microflakes or silver nanoparticles. The antenna has a compact size of 18 × 20 × 0.12 mm3 and adopts a gradient feeder and a radiation patch with three folding slots. It was fabricated on transparent and flexible poly(ethylene terephthalate) film substrates, using screen printing and inkjet printing. The measurement results demonstrated that the fabricated antennas could cover the UWB band (2.35-10.93 GHz) while efficiently filtering out interferences from the C-band downlink satellite system (3.43-4.21 GHz), wireless local area networks (4.66-5.29 GHz), and X-band uplink satellite system (6.73-8.02 GHz), which was consistent with the simulation results. The bendability and radiation safety of the antennas were evaluated, proving their feasibility for usage under bending conditions and near the human body. Additionally, it was found that the screen-printed antenna performed better after bending. The research is expected to provide guidance on designing flexible antennas that are both safe to wear and easily conformable.

Anti-swelling Microporous Membrane for High-capacity and Long-life Zn-I2 Batteries.

Zinc-iodine (Zn-I2) batteries are gaining popularity due to cost-effectiveness and ease of manufacturing. However, challenges like polyiodide shuttle effect and Zn dendrite growth hinder their practical application. Here, we report a cation exchange membrane to simultaneously prevent the polyiodide shuttle effect and regulate Zn2+ deposition. Comprised of rigid polymers, this membrane shows superior swelling resistance and ion selectivity compared to commercial Nafion. The resulting Zn-I2 battery exhibits a high Coulombic efficiency of 99.4% and low self-discharge rate of 4.47% after 48 h rest. By directing a uniform Zn2+ flux, the membrane promotes a homogeneous electric field, resulting in a dendrite-free Zn surface. Moreover, its microporous structure enables pre-adsorption of additional active materials prior to battery assembly, boosting battery capacity to 287 mA h g-1 at 0.1 A g-1. At 2 A g-1, the battery exhibits a steady running for 10,000 cycles with capacity retention up to 96.1%, demonstrating high durability of the membrane. The practicality of the membrane is validated via a high loading (35 mg cm-2) pouch cell with impressive cycling stability, paving a way for membrane design towards advanced Zn-I2 batteries.

An Enzymatic Oxidation Cascade Converts δ-Thiolactone Anthracene to Anthraquinone in the Biosynthesis of Anthraquinone-Fused Enediynes.

Anthraquinone-fused enediynes are anticancer natural products featuring a DNA-intercalating anthraquinone moiety. Despite recent insights into anthraquinone-fused enediyne (AQE) biosynthesis, the enzymatic steps involved in anthraquinone biogenesis remain to be elucidated. Through a combination of in vitro and in vivo studies, we demonstrated that a two-enzyme system, composed of a flavin adenine dinucleotide (FAD)-dependent monooxygenase (DynE13) and a cofactor-free enzyme (DynA1), catalyzes the final steps of anthraquinone formation by converting δ-thiolactone anthracene to hydroxyanthraquinone. We showed that the three oxygen atoms in the hydroxyanthraquinone originate from molecular oxygen (O2), with the sulfur atom eliminated as H2S. We further identified the key catalytic residues of DynE13 and A1 by structural and site-directed mutagenesis studies. Our data support a catalytic mechanism wherein DynE13 installs two oxygen atoms with concurrent desulfurization and decarboxylation, whereas DynA1 acts as a cofactor-free monooxygenase, installing the final oxygen atom in the hydroxyanthraquinone. These findings establish the indispensable roles of DynE13 and DynA1 in AQE biosynthesis and unveil novel enzymatic strategies for anthraquinone formation.

Artificial intelligence applied to 'omics data in liver disease: towards a personalised approach for diagnosis, prognosis and treatment.

Advancements in omics technologies and artificial intelligence (AI) methodologies are fuelling our progress towards personalised diagnosis, prognosis and treatment strategies in hepatology. This review provides a comprehensive overview of the current landscape of AI methods used for analysis of omics data in liver diseases. We present an overview of the prevalence of different omics levels across various liver diseases, as well as categorise the AI methodology used across the studies. Specifically, we highlight the predominance of transcriptomic and genomic profiling and the relatively sparse exploration of other levels such as the proteome and methylome, which represent untapped potential for novel insights. Publicly available database initiatives such as The Cancer Genome Atlas and The International Cancer Genome Consortium have paved the way for advancements in the diagnosis and treatment of hepatocellular carcinoma. However, the same availability of large omics datasets remains limited for other liver diseases. Furthermore, the application of sophisticated AI methods to handle the complexities of multiomics datasets requires substantial data to train and validate the models and faces challenges in achieving bias-free results with clinical utility. Strategies to address the paucity of data and capitalise on opportunities are discussed. Given the substantial global burden of chronic liver diseases, it is imperative that multicentre collaborations be established to generate large-scale omics data for early disease recognition and intervention. Exploring advanced AI methods is also necessary to maximise the potential of these datasets and improve early detection and personalised treatment strategies.

Influence of tumor thrombus morphology on the surgical complexity in renal cell carcinoma with inferior vena cava tumor thrombus: a single-center, large-sample study from China.

BACKGROUND: The morphology of tumor thrombus varies from person to person and it may affect surgical methods and tumor prognosis. However, studies on the morphology of tumor thrombus are limited. The purpose of our study was to evaluate the impact of tumor thrombus morphology on surgical complexity. METHODS: We retrospectively reviewed the clinical data of 229 patients with renal cell carcinoma combined with inferior vena cava (IVC) tumor thrombus who underwent surgical treatment at Peking University Third Hospital between January 2014 and December 2021. The patients were divided into floating morphology (107 patients) and filled morphology (122 patients) tumor thrombi groups. Chi-square and Mann-Whitney U tests were used for categorical and continuous variables, respectively. Postoperative complications were evaluated using the Clavien-Dindo surgical complication classification method. RESULTS: Patients with filled morphology tumor thrombus required more surgical techniques than those with floating morphology tumor thrombus, which was reflected in more open surgeries (P < 0.001), more IVC interruptions (P <0.001), lesser use of the delayed occlusion of the proximal inferior vena cava (DOPI) technique (P < 0.001), and a greater need for cut-off of the short hepatic vein (P < 0.001) and liver dissociation (P = 0.001). Filled morphology significantly increased the difficulty of surgery in patients with renal cell carcinoma with tumor thrombus, reflected in longer operation time (P < 0.001), more surgical blood loss (P <0.001), more intra-operative blood transfusion (P < 0.001), and longer postoperative hospital stay (P < 0.001). Filled morphology tumor thrombus also led to more postoperative complications (53% vs. 20%; P < 0.001). CONCLUSION: Compared with floating morphology thrombus, filled morphology thrombus significantly increased the difficulty of surgery in patients with renal cell carcinoma with IVC tumor thrombus.

Clinical Deployment of Machine Learning Tools in Transplant Medicine: What Does the Future Hold?

Medical applications of machine learning (ML) have shown promise in analyzing patient data to support clinical decision-making and provide patient-specific outcomes. In transplantation, several applications of ML exist which include pretransplant: patient prioritization, donor-recipient matching, organ allocation, and posttransplant outcomes. Numerous studies have shown the development and utility of ML models, which have the potential to augment transplant medicine. Despite increasing efforts to develop robust ML models for clinical use, very few of these tools are deployed in the healthcare setting. Here, we summarize the current applications of ML in transplant and discuss a potential clinical deployment framework using examples in organ transplantation. We identified that creating an interdisciplinary team, curating a reliable dataset, addressing the barriers to implementation, and understanding current clinical evaluation models could help in deploying ML models into the transplant clinic setting.

A cyclic di-GMP-binding adaptor protein interacts with a N5-glutamine methyltransferase to regulate the pathogenesis in Xanthomonas citri subsp. citri.

The second messenger cyclic diguanylate monophosphate (c-di-GMP) regulates a wide range of bacterial behaviours through diverse mechanisms and binding receptors. Single-domain PilZ proteins, the most widespread and abundant known c-di-GMP receptors in bacteria, act as trans-acting adaptor proteins that enable c-di-GMP to control signalling pathways with high specificity. This study identifies a single-domain PilZ protein, XAC3402 (renamed N5MapZ), from the phytopathogen Xanthomonas citri subsp. citri (Xcc), which modulates Xcc virulence by directly interacting with the methyltransferase HemK. Through yeast two-hybrid, co-immunoprecipitation and immunofluorescent staining, we demonstrated that N5MapZ and HemK interact directly under both in vitro and in vivo conditions, with the strength of the protein-protein interaction decreasing at high c-di-GMP concentrations. This finding distinguishes N5MapZ from other characterized single-domain PilZ proteins, as it was previously known that c-di-GMP enhances the interaction between those single-domain PilZs and their protein partners. This observation is further supported by the fact that the c-di-GMP binding-defective mutant N5MapZR10A can interact with HemK to inhibit the methylation of the class 1 translation termination release factor PrfA. Additionally, we found that HemK plays an important role in Xcc pathogenesis, as the deletion of hemK leads to extensive phenotypic changes, including reduced virulence in citrus plants, decreased motility, production of extracellular enzymes and stress tolerance. Gene expression analysis has revealed that c-di-GMP and the HemK-mediated pathway regulate the expression of multiple virulence effector proteins, uncovering a novel regulatory mechanism through which c-di-GMP regulates Xcc virulence by mediating PrfA methylation via the single-domain PilZ adaptor protein N5MapZ.

Whole-genome Sequencing Reveals Autooctoploidy in Chinese Sturgeon and Its Evolutionary Trajectories.

The order Acipenseriformes, which includes sturgeons and paddlefishes, represents "living fossils" with complex genomes that are good models for understanding whole-genome duplication (WGD) and ploidy evolution in fishes. Here, we sequenced and assembled the first high-quality chromosome-level genome for the complex octoploid Acipenser sinensis (Chinese sturgeon), a critically endangered species that also represents a poorly understood ploidy group in Acipenseriformes. Our results show that A. sinensis is a complex autooctoploid species containing four kinds of octovalents (8n), a hexavalent (6n), two tetravalents (4n), and a divalent (2n). An analysis taking into account delayed rediploidization reveals that the octoploid genome composition of Chinese sturgeon results from two rounds of homologous WGDs, and further provides insights into the timing of its ploidy evolution. This study provides the first octoploid genome resource of Acipenseriformes for understanding ploidy compositions and evolutionary trajectories of polyploid fishes.

Deep learning-based pathway-centric approach to characterize recurrent hepatocellular carcinoma after liver transplantation.

BACKGROUND: Liver transplantation (LT) is offered as a cure for Hepatocellular carcinoma (HCC), however 15-20% develop recurrence post-transplant which tends to be aggressive. In this study, we examined the transcriptome profiles of patients with recurrent HCC to identify differentially expressed genes (DEGs), the involved pathways, biological functions, and potential gene signatures of recurrent HCC post-transplant using deep machine learning (ML) methodology. MATERIALS AND METHODS: We analyzed the transcriptomic profiles of primary and recurrent tumor samples from 7 pairs of patients who underwent LT. Following differential gene expression analysis, we performed pathway enrichment, gene ontology (GO) analyses and protein-protein interactions (PPIs) with top 10 hub gene networks. We also predicted the landscape of infiltrating immune cells using Cibersortx. We next develop pathway and GO term-based deep learning models leveraging primary tissue gene expression data from The Cancer Genome Atlas (TCGA) to identify gene signatures in recurrent HCC. RESULTS: The PI3K/Akt signaling pathway and cytokine-mediated signaling pathway were particularly activated in HCC recurrence. The recurrent tumors exhibited upregulation of an immune-escape related gene, CD274, in the top 10 hub gene analysis. Significantly higher infiltration of monocytes and lower M1 macrophages were found in recurrent HCC tumors. Our deep learning approach identified a 20-gene signature in recurrent HCC. Amongst the 20 genes, through multiple analysis, IL6 was found to be significantly associated with HCC recurrence. CONCLUSION: Our deep learning approach identified PI3K/Akt signaling as potentially regulating cytokine-mediated functions and the expression of immune escape genes, leading to alterations in the pattern of immune cell infiltration. In conclusion, IL6 was identified to play an important role in HCC recurrence.

Discrimination of polysorbate 20 by high-performance liquid chromatography-charged aerosol detection and characterization for components by expanding compound database and library.

Analyzing polysorbate 20 (PS20) composition and the impact of each component on stability and safety is crucial due to formulation variations and individual tolerance. The similar structures and polarities of PS20 components make accurate separation, identification, and quantification challenging. In this work, a high-resolution quantitative method was developed using single-dimensional high-performance liquid chromatography (HPLC) with charged aerosol detection (CAD) to separate 18 key components with multiple esters. The separated components were characterized by ultra-high-performance liquid chromatography-quadrupole time-of-flight mass spectrometry (UHPLC-Q-TOF-MS) with an identical gradient as the HPLC-CAD analysis. The polysorbate compound database and library were expanded over 7-time compared to the commercial database. The method investigated differences in PS20 samples from various origins and grades for different dosage forms to evaluate the composition-process relationship. UHPLC-Q-TOF-MS identified 1329 to 1511 compounds in 4 batches of PS20 from different sources. The method observed the impact of 4 degradation conditions on peak components, identifying stable components and their tendencies to change. HPLC-CAD and UHPLC-Q-TOF-MS results provided insights into fingerprint differences, distinguishing quasi products.

A compact tri-notched flexible UWB antenna based on an inkjet-printable and plasma-activated silver nano ink.

The rapid development of ultrawideband (UWB) communication systems has resulted in increasing performance requirements for the antenna system. In addition to a wide bandwidth, fast propagation rates and compact dimensions, flexibility, wearability or portability are also desirable for UWB antennas, as are excellent notch characteristics. Although progress has been made in the development of flexible/wearable antennas desired notch properties are still rather limited. Moreover, most presently available flexible UWB antennas are fabricated using environmentally not attractive subtractive etching-based processes. The usage of facile additive sustainably inkjet printing processes also utilizing low temperature plasma-activated conductive inks is rarely reported. In addition, the currently used tri-notched flexible UWB antenna designs have a relatively large footprint, which poses difficulties when integrated into miniaturized and compact communication devices. In this work, a silver nano ink is used to fabricate the antenna via inkjet printing and an efficient plasma sintering procedure. For the targeted UWB applications miniaturized tri-notched flexible antenna is realized on a flexible polyethylene terephthalate (PET) substrate with a compact size of 17.6 mm × 16 mm × 0.12 mm. The antenna operates in the UWB frequency band (2.9-10.61 GHz), and can shield interferences from WiMAX (3.3-3.6 GHz), WLAN (5.150-5.825 GHz) and X-uplink (7.9-8.4 GHz) bands, as well as exhibits a certain of bendability. Three nested "C" slots of different sizes were adopted to achieve notch features. The simulation and test results demonstrate that the proposed antenna can generate signal radiation in the desired UWB frequency band while retaining the desired notch properties and having acceptable SAR values on-body, making it a viable candidate for usage in flexible or wearable communication transmission devices. The research provides a facile and highly efficient method for fabricating flexible/wearable UWB antennas, that is, the effective combination of inkjet printing processing, flexible substrates, low temperature-activated conductive ink and antenna structure design.

Permanent fluidic magnets for liquid bioelectronics.

Brownian motion allows microscopically dispersed nanoparticles to be stable in ferrofluids, as well as causes magnetization relaxation and prohibits permanent magnetism. Here we decoupled the particle Brownian motion from colloidal stability to achieve a permanent fluidic magnet with high magnetization, flowability and reconfigurability. The key to create such permanent fluidic magnets is to maintain a stable magnetic colloidal fluid by using non-Brownian magnetic particles to self-assemble a three-dimensional oriented and ramified magnetic network structure in the carrier fluid. This structure has high coercivity and permanent magnetization, with long-term magnetization stability. We establish a scaling theory model to decipher the permanent fluid magnet formation criteria and formulate a general assembly guideline. Further, we develop injectable and retrievable permanent-fluidic-magnet-based liquid bioelectronics for highly sensitive, self-powered wireless cardiovascular monitoring. Overall, our findings highlight the potential of permanent fluidic magnets as an ultrasoft material for liquid devices and systems, from bioelectronics to robotics.

Radiomic signatures associated with tumor immune heterogeneity predict survival in locally recurrent nasopharyngeal carcinoma.

BACKGROUND: The prognostic value of traditional clinical indicators for locally recurrent nasopharyngeal carcinoma is limited because of their inability to reflect intratumor heterogeneity. We aimed to develop a radiomic signature to reveal tumor immune heterogeneity and predict survival in locally recurrent nasopharyngeal carcinoma. METHODS: This multicenter, retrospective study included 921 patients with locally recurrent nasopharyngeal carcinoma. A machine learning signature and nomogram based on pretreatment magnetic resonance imaging features were developed for predicting overall survival in a training cohort and validated in 2 independent cohorts. A clinical nomogram and an integrated nomogram were constructed for comparison. Nomogram performance was evaluated by concordance index and receiver operating characteristic curve analysis. Accordingly, patients were classified into risk groups. The biological characteristics and immune infiltration of the signature were explored by RNA-sequencing analysis. RESULTS: The machine learning signature and nomogram demonstrated comparable prognostic ability to a clinical nomogram, achieving concordance indexes of 0.729, 0.718, and 0.731 in the training, internal, and external validation cohorts, respectively. Integration of the signature and clinical variables statistically improved the predictive performance. The proposed signature effectively distinguished patients between risk groups with statistically distinct overall survival rates. Subgroup analysis indicated the recommendation of local salvage treatments for low-risk patients. Exploratory RNA-sequencing analysis revealed differences in interferon response and lymphocyte infiltration between risk groups. CONCLUSIONS: A magnetic resonance imaging-based radiomic signature predicted overall survival more accurately. The proposed signature associated with tumor immune heterogeneity may serve as a valuable tool to facilitate prognostic stratification and guide individualized management for locally recurrent nasopharyngeal carcinoma patients.

Fine-Scale Quantification of Absorbed Photosynthetically Active Radiation (APAR) in Plantation Forests with 3D Radiative Transfer Modeling and LiDAR Data.

Quantifying the relationship between light and stands or individual trees is of great significance in understanding tree competition, improving forest productivity, and comprehending ecological processes. However, accurately depicting the spatiotemporal variability of light under complex forest structural conditions poses a challenge, especially for precise forest management decisions that require a quantitative study of the relationship between fine-scale individual tree structure and light. 3D RTMs (3-dimensional radiative transfer models), which accurately characterize the interaction between solar radiation and detailed forest scenes, provide a reliable means for depicting such relationships. This study employs a 3D RTM and LiDAR (light detection and ranging) data to characterize the light environment of larch plantations at a fine spatiotemporal scale, further investigating the relationship between absorbed photosynthetically active radiation (APAR) and forest structures. The impact of specific tree structural parameters, such as crown diameter, crown area, crown length, crown ratio, crown volume, tree height, leaf area index, and a distance parameter assessing tree competition, on the daily-scale cumulative APAR per tree was investigated using a partial least squares regression (PLSR) model. Furthermore, variable importance in projection (VIP) was also calculated from the PLSR. The results indicate that among the individual tree structure parameters, crown volume is the most important one in explaining individual tree APAR (VIP = 4.19), while the competition from surrounding trees still plays a role in explaining individual tree APAR to some extent (VIP = 0.15), and crown ratio contributes the least (VIP = 0.03). Regarding the spatial distribution of trees, the average cumulative APAR per tree of larch plots does not increase with an increase in canopy gap fraction. Tree density and average cumulative APAR per tree were fitted using a natural exponential equation, with a coefficient of determination (R2 = 0.89), and a small mean absolute percentage error (MAPE = 0.03). This study demonstrates the potential of combining 3D RTM with LiDAR data to quantify fine-scale APAR in plantations, providing insights for optimizing forest structure, enhancing forest quality, and implementing precise forest management practices, such as selective breeding for superior tree species.

Streptomyces sungeiensis SD3 as a Microbial Chassis for the Heterologous Production of Secondary Metabolites.

We present the newly isolated Streptomyces sungeiensis SD3 strain as a promising microbial chassis for heterologous production of secondary metabolites. S. sungeiensis SD3 exhibits several advantageous traits as a microbial chassis, including genetic tractability, rapid growth, susceptibility to antibiotics, and metabolic capability supporting secondary metabolism. Genomic and transcriptomic sequencing unveiled the primary metabolic capabilities and secondary biosynthetic pathways of S. sungeiensis SD3, including a previously unknown pathway responsible for the biosynthesis of streptazone B1. The unique placement of S. sungeiensis SD3 in the phylogenetic tree designates it as a type strain, setting it apart from other frequently employed Streptomyces chassis. This distinction makes it the preferred chassis for expressing biosynthetic gene clusters (BGCs) derived from strains within the same phylogenetic or neighboring phylogenetic clade. The successful expression of secondary biosynthetic pathways from a closely related yet slow-growing strain underscores the utility of S. sungeiensis SD3 as a heterologous expression chassis. Validation of CRISPR/Cas9-assisted genetic tools for chromosomal deletion and insertion paved the way for further strain improvement and BGC refactoring through rational genome editing. The addition of S. sungeiensis SD3 to the heterologous chassis toolkit will facilitate the discovery and production of secondary metabolites.

Insight into the Types of Alkanolamines on the Properties of Copper(II) Formate-Based Conductive Ink.

Conductive inks are one of the most important functional materials for printed flexible electronic devices, and their properties determine the methods of subsequent patterning and metallization. In comparison with copper nanoparticle or nanowire inks, copper particle-free inks employing copper(II) formate (Cuf) as a precursor have attracted the interest of researchers due to their flexibility in preparation, excellent stability, and lower conversion temperature. Alkanolamines can provide Cuf with excellent solubility in alcohols while being less toxic and having a certain reducibility, making them preferable ligands in comparison with aliphatic amines and pyridine. However, there have been few studies on the effects of the alkanolamine types on the performance of Cuf inks. Also, the decomposition mechanism of copper-alkanolamine complex inks is not clear. In this work, different kinds of alkanolamines were chosen as ligands to formulate Cuf inks to address the mentioned issues. The influences of amine types on the stability, wettability, thermal decomposition behavior, and electrical performance of the formulated Cuf particle-free inks were investigated in detail. The results show that the utilization of alkanolamines could provide Cuf with excellent solubility in alcohols, resulting in an ink with good stability and favorable wetting properties. The thermal decomposition temperature and electrical performance of the formulated copper ink are largely dependent on the amine used. When amines with a longer carbon chain and more branches were utilized to prepare the ink, a decreased decomposition temperature was observed on the derived inks because of the steric hindrance effect. Copper films with good morphology and conductivity could be obtained at low temperatures by selecting the appropriate alkanolamine. Copper particle-free conductive ink from 2-amino-2-methyl-1-propanol demonstrated better morphology and electrical performance (16.09 µΩ·cm) and was successfully used for conductive circuits by direct-writing.

Initial cyclic-di-GMP upregulation triggers sporadic cellular expansion leading to improved cellular survival.

Bacterial second messenger c-di-GMP upregulation is associated with the transition from planktonic to sessile microbial lifestyle, inhibiting cellular motility, and virulence. However, in-depth elucidation of the cellular processes resulting from c-di-GMP upregulation has not been fully explored. Here, we report the role of upregulated cellular c-di-GMP in promoting planktonic cell growth of Escherichia coli K12 and Pseudomonas aeruginosa PAO1. We found a rapid expansion of cellular growth during initial cellular c-di-GMP upregulation, resulting in a larger planktonic bacterial population. The initial increase in c-di-GMP levels promotes bacterial swarming motility during the growth phase, which is subsequently inhibited by the continuous increase of c-di-GMP, and ultimately facilitates the formation of biofilms. We demonstrated that c-di-GMP upregulation triggers key bacterial genes linked to bacterial growth, swarming motility, and biofilm formation. These genes are mainly controlled by the master regulatory genes csgD and csrA. This study provides us a glimpse of the bacterial behavior of evading potential threats through adapting lifestyle changes via c-di-GMP regulation.

A PilZ domain protein interacts with the transcriptional regulator HinK to regulate type VI secretion system in Pseudomonas aeruginosa.

Type VI secretion systems (T6SS) are bacterial macromolecular complexes that secrete effectors into target cells or the extracellular environment, leading to the demise of adjacent cells and providing a survival advantage. Although studies have shown that the T6SS in Pseudomonas aeruginosa is regulated by the Quorum Sensing system and second messenger c-di-GMP, the underlying molecular mechanism remains largely unknown. In this study, we discovered that the c-di-GMP-binding adaptor protein PA0012 has a repressive effect on the expression of the T6SS HSI-I genes in P. aeruginosa PAO1. To probe the mechanism by which PA0012 (renamed TssZ, Type Six Secretion System -associated PilZ protein) regulates the expression of HSI-I genes, we conducted yeast two-hybrid screening and identified HinK, a LasR-type transcriptional regulator, as the binding partner of TssZ. The protein-protein interaction between HinK and TssZ was confirmed through co-immunoprecipitation assays. Further analysis suggested that the HinK-TssZ interaction was weakened at high c-di-GMP concentrations, contrary to the current paradigm wherein c-di-GMP enhances the interaction between PilZ proteins and their partners. Electrophoretic mobility shift assays revealed that the non-c-di-GMP-binding mutant TssZR5A/R9A interacts directly with HinK and prevents it from binding to the promoter of the quorum-sensing regulator pqsR. The functional connection between TssZ and HinK is further supported by observations that TssZ and HinK impact the swarming motility, pyocyanin production, and T6SS-mediated bacterial killing activity of P. aeruginosa in a PqsR-dependent manner. Together, these results unveil a novel regulatory mechanism wherein TssZ functions as an inhibitor that interacts with HinK to control gene expression.