The zinc ion concentration dynamically regulated by an ionophore in the outer Helmholtz layer for stable Zn anode.

The Zn dendrite limits the practical application of aqueous zinc-ion batteries in the large-scale energy storage systems. To suppress the growth of Zn dendrites, a zinc ionophore of hydroxychloroquine (defined as HCQ) applied in vivo treatment is investigated as the electrolyte additive. HCQ dynamically regulates zinc ion concentration in the outer Helmholtz layer, promoting even Zn plating at the anode/electrolyte interface. This is evidenced by the scanning electron microscopy, which delivers planar Zn plating after cycling. It is further supported by the X-ray diffraction spectroscopy, which reveals the growth of Zn (002) plane. Additionally, the reduced production of H2 during Zn plating/stripping is detected by the in-situ differential electrochemical mass spectrometry (DEMS), which shows the resistance of Zn (002) to hydrogen evolution reaction. The mechanism of dynamic regulation for zinc ion concentration is demonstrated by the in-situ optical microscopy. The hydrated zinc ion can be further plated more rapidly to the uneven location than the case in other regions, which is resulted from the dynamic regulation for zinc ion concentration. Therefore, the uniform Zn plating is formed. A cycling life of 1100 h is exhibited in the Zn||Zn symmetric cell at 1.6 mA cm-2 with the capacity of 1.6 mAh cm-2. The Zn||Cu battery exhibits a cycling life of 200 cycles at 4 mA cm-2 with a capacity of 4 mAh cm-2 and the average Coulombic efficiency is larger than 99 %. The Zn||VO2 battery with HCQ modified electrolyte can operate for 1500 cycles at 4 A g-1 with a capacity retention of 90 %. This strategy in the present work is wished to advance the development of zinc-ion batteries for practical application.

Cross-sectional study of hepatitis B virus infection in female breast cancer patients in China for the first time diagnosed.

BACKGROUND: The correlation between breast cancer and hepatitis B virus (HBV) remains inconclusive. This study aims to explore the serological status of HBV infection and past infection in different age groups of female breast cancer patients, patients with benign breast diseases, and individuals undergoing routine physical examinations. METHODS: Serum data on HBV serological markers were collected and analyzed from 6072 female breast cancer patients first diagnosed from September 2012 to July 2020 at the First Affiliated Hospital of Chongqing Medical University, along with 4019 women with benign breast diseases and 54,740 healthy females undergoing routine physical examinations in the same period. The data were stratified by age for comparison between groups. RESULTS: The prevalence of HBV infection and past infection in the breast cancer group (7.9%, 55.1%) was higher than that in the benign breast disease group (6.5%, 39.1%) and the healthy females group(5.0%, 17.6%);the rate of only HBV surface antibody positivity (HBsAb ( +)) in the breast cancer group (10.3%) was lower than that in the benign breast disease group (26.9%) and the healthy females group (49.2%), with significant differences between the three groups (p < 0.05). Stratified by age, the prevalence of HBV infection in the breast cancer group (8%, 8.9%) and benign breast disease group (7.75%, 8.1%)was higher than that in the healthy females group (4.5%, 6.3%) in the 30-39 and 40-49 age group, respectively. The past infection rate of HBV in the breast cancer group (24.8%, 45.0%) was higher than that in the benign breast disease group (16.1%, 35.4%) in the ≤ 29 and 30-39 age group, respectively.. The past infection rate of HBV in the breast cancer group was higher than that in the healthy females group in all age groups, while the rate of only HBsAb ( +) in the breast cancer group was lower than that in the benign breast disease group and the routine physical examination group in all age groups. CONCLUSIONS: Breast cancer women and women with benign breast diseases have higher rates of hepatitis B virus infection and previous infections, with more significant differences among middle-aged women. Breast cancer women and women with benign breast diseases have lower rates of only HBsAb ( +) for HBV.

Inhibition of autophagy via 3-methyladenine alleviates the progression of preeclampsia.

Autophagy is a cellular mechanism for self-renewal that involves the breakdown of cytoplasmic proteins or organelles within lysosomes. Although preeclampsia (PE) exhibits several characteristics that could imply disrupted autophagy, there is limited evidence supporting the notion that impaired placental autophagy directly causes PE, as indicated by differential expression profiling of whole placental tissue. In this study, we aim to explore the significance of autophagy in maintaining pregnancy and its association with PE. First, the RNA-seq results show that 218 genes are differentially expressed in placentas from preeclamptic pregnancies. Notably, KEGG pathway analysis reveals significant enrichment of genes related to autophagy-related signaling pathways, including the PI3K-Akt signaling pathway, the AMPK signaling pathway, and the mTOR signaling pathway. Additionally, our findings indicate an increase in autophagy in placentas from pregnancies complicated by preeclampsia as well as in trophoblasts subjected to hypoxic conditions. Next, we examine the impact of 3-methyladenine (3-MA), a targeted inhibitor of autophagy, on the progression of PE. The administration of 3-MA profoundly alleviates the severity of PE-like symptoms in rats subjected to reduced uterine perfusion pressure (RUPP). The findings from our study suggest that inhibiting autophagy may serve as a promising approach for adjuvant chemotherapy for PE.

Stereochemical Control of Redox CoII/CoIII-Cages with Switchable Cotton Effects Based on Labile-Static States.

The structural dynamics of artificial assemblies, in aspects such as molecular recognition and structural transformation, provide us with a blueprint to achieve bioinspired applications. Here, we describe the assembly of redox-switchable chiral metal-organic cages Λ8/Δ8-[Pd6(CoIIL3)8]28+ and Λ8/Δ8-[Pd6(CoIIIL3)8]36+. These isomeric cages demonstrate an on-off chirality logic gate controlled by their chemical and stereostructural dynamics tunable through redox transitions between the labile CoII-state and static CoIII-state with a distinct Cotton effect. The transition between different states is enabled by a reversible redox process and chiral recognition originating in the tris-chelate Co-centers. All cages in two states are thoroughly characterized by NMR, ESI-MS, CV, CD, and X-ray crystallographic analysis, which clarify their redox-switching behaviors upon chemical reduction/oxidation. The stereochemical lability of the CoII-center endows the Λ8/Δ8-CoII-cages with efficient chiral-induction by enantiomeric guests, leading to enantiomeric isomerization to switch between Λ8/Δ8-CoII-cages, which can be stabilized by oxidation to their chemically inert forms of Λ8/Δ8-CoIII-cages. Kinetic studies reveal that the isomerization rate of the Δ8-CoIII-cage is at least an order of magnitude slower than that of the Δ8-CoII-cage even at an elevated temperature, while its activation energy is 16 kcal mol-1 higher than that of the CoII-cage.

Suppression of frequency-mixing effect for pm-level heterodyne interferometers based on "zero coupling" optical path length control.

Optical path length (OPL) noise resulting from stray light significantly constrains interferometry displacement measurements in the low-frequency band. This paper presents an analytical model considering the presence of stray light in heterodyne laser interferometers. Due to the cyclic nonlinear coupling effect, there will be some special OPLs of stray light, minimizing the frequency-mixing impact to zero. Consequently, we propose a noise suppression scheme that locks the OPL of stray light at the zero coupling point. Therefore, we significantly enhanced the interference displacement measurement noise within the low-frequency band. Experimental results show that the interferometer achieves a displacement noise level lower than 6 pm/Hz1/2 covering 1 mHz.

DOT1L/H3K79me2 represses HIV-1 reactivation via recruiting DCAF1.

DOT1L mediates the methylation of histone H3 at lysine 79 and, in turn, the transcriptional activation or repression in a context-dependent manner, yet the regulatory mechanisms and functions of DOT1L/H3K79me remain to be fully explored. Following peptide affinity purification and proteomic analysis, we identified that DCAF1-a component of the E3 ligase complex involved in HIV regulation-is associated with H3K79me2 and DOT1L. Interestingly, blocking the expression or catalytic activity of DOT1L or repressing the expression of DCAF1 significantly enhances the tumor necrosis factor alpha (TNF-α)/nuclear factor κB (NF-κB)-induced reactivation of the latent HIV-1 genome. Mechanistically, upon TNF-α/NF-κB activation, DCAF1 is recruited to the HIV-1 long terminal repeat (LTR) by DOT1L and H3K79me2. Recruited DCAF1 subsequently induces the ubiquitination of NF-κB and restricts its accumulation at the HIV-1 LTR. Altogether, our findings reveal a feedback modulation of HIV reactivation by DOT1L-mediated histone modification regulation and highlight the potential of targeting the DOT1L/DCAF1 axis as a therapeutic strategy for HIV treatment.

Comparison of learning curves and related postoperative indicators between endoscopic and robotic thyroidectomy: a systematic review and meta-analysis.

BACKGROUD: Endoscopic thyroidectomy (ET) and robotic thyroidectomy (RT) yield similar perioperative outcomes. This study investigated how the learning curve (LC) affects perioperative outcomes between ET and RT, identifying factors that influence the LC. MATERIALS AND METHODS: Two researchers individually searched PubMed, EMBASE, Web of Science, and Cochrane Library for relevant studies published until February 2024. The Newcastle-Ottawa Scale assessed study quality. Random effects model was used to compute the odds ratio and weighted mean difference (WMD). Poisson regression comparison of the number of surgeries (NLC) was required for ET and RT to reach the stable stage of the LC. Heterogeneity was measured using Cochran's Q. Publication bias was tested using funnel plots, and sensitivity analysis assessed findings robustness. Subgroup analysis was done by operation type and patient characteristics. RESULTS: This meta-analysis involved 33 studies. The drainage volume of ET was higher than that of RT (WMD=-17.56 [30.22, -4.49]). After reaching the NLC, the operation time of ET and RT was shortened (ET: WMD=28.15[18.04, 38.26]; RT: WMD=38.53[29.20, 47.86]). Other perioperative outcomes also improved to varying degrees. Notably, RT showed more refined central lymph node resection(5.67 vs. 4.71), less intraoperative bleeding (16.56 mL vs. 42.30 mL), and incidence of transient recurrent laryngeal nerve injury(24.59 vs. 26.77). The NLC of RT was smaller than that of ET(Incidence-rate ratios [IRR]=0.64[0.57, 0.72]). CUSUM analysis (ET: IRR=0.84[0.72, 0.99]; RT: IRR=0.55[0.44, 0.69]) or a smaller number of respondents (ET: IRR=0.26[0.15, 0.46]; RT: IRR=0.51[0.41, 0.63]) was associated with smaller NLC. In RT, transoral approach (IRR=2.73[1.96, 4.50]; IRR=2.48[1.61, 3.84]) and retroauricular approach (RAA) (IRR=2.13[1.26, 3.60]; IRR=1.78[1.04, 3.05]) had smaller NLC compared to bilateral axillo-breast and transaxillary approach (TAA). In ET, the NLC of RAA was smaller than that of TAA (IRR=1.61[1.04, 2.51]), breast approach(IRR=1.67[1.06, 2.64]), and subclavian approach(IRR=1.80[1.03, 3.14]). CONCLUSIONS: Rich surgical experience can improve surgical results of ET and RT. After reaching the NLC, the perioperative outcomes of RT are better than those of ET. Study subjects, surgical approaches, and analysis methods can affect NLC.

A comprehensive analysis of antibiotic resistance genes in the giant panda gut.

In this study, we have successfully constructed a comprehensive database of metagenome-assembled genomes (MAGs) pertaining to the gut microbiota of the giant panda. Through our analysis, we have identified significant reservoirs of antibiotic resistance genes (ARGs), namely Escherichia coli, Citrobacter portucalensis, and Klebsiella pneumoniae. Furthermore, we have elucidated the primary contributors to ARGs, including Streptococcus alactolyticus and Clostridium SGBP116, in both captive and wild pandas. Additionally, our findings have demonstrated a higher prevalence of ARGs in the metagenome, with notable expression of the RPOB2 gene in S. alactolyticus. Crucially, 1217 ARGs shared homology with human gut ARGs, underscoring the interaction relationship between pandas and human microbiomes. These findings are instrumental in understanding the antibiotic resistance landscape in the giant panda's gut, providing a framework for developing strategies to combat antibiotic resistance and safeguard the health of this endangered species.

Advancements and Perspectives in Optical Biosensors.

Optical biosensors exhibit immense potential, offering extraordinary possibilities for biosensing due to their high sensitivity, reusability, and ultrafast sensing capabilities. This review provides a concise overview of optical biosensors, encompassing various platforms, operational mechanisms, and underlying physics, and it summarizes recent advancements in the field. Special attention is given to plasmonic biosensors and metasurface-based biosensors, emphasizing their significant performance in bioassays and, thus, their increasing attraction in biosensing research, positioning them as excellent candidates for lab-on-chip and point-of-care devices. For plasmonic biosensors, we emphasize surface plasmon resonance (SPR) and its subcategories, along with localized surface plasmon resonance (LSPR) devices and surface enhance Raman spectroscopy (SERS), highlighting their ability to perform diverse bioassays. Additionally, we discuss recently emerged metasurface-based biosensors. Toward the conclusion of this review, we address current challenges, opportunities, and prospects in optical biosensing. Considering the advancements and advantages presented by optical biosensors, it is foreseeable that they will become a robust and widespread platform for early disease diagnostics.

Diffusion kurtosis imaging-based habitat analysis identifies high-risk molecular subtypes and heterogeneity matching in diffuse gliomas.

OBJECTIVE: High-risk types of diffuse gliomas in adults include isocitrate dehydrogenase (IDH) wild-type glioblastomas and grade 4 astrocytomas. Achieving noninvasive prediction of high-risk molecular subtypes of gliomas is important for personalized and precise diagnosis and treatment. METHODS: We retrospectively collected data from 116 patients diagnosed with adult diffuse gliomas. Multiple high-risk molecular markers were tested, and various habitat models and whole-tumor models were constructed based on preoperative routine and diffusion kurtosis imaging (DKI) sequences to predict high-risk molecular subtypes of gliomas. Feature selection and model construction utilized Least absolute shrinkage and selection operator (LASSO) and support vector machine (SVM). Finally, the Wilcoxon rank-sum test was employed to explore the correlation between habitat quantitative features (intra-tumor heterogeneity score，ITH score) and heterogeneity, as well as high-risk molecular subtypes. RESULTS: The results showed that the habitat analysis model based on DKI performed remarkably well (with AUC values reaching 0.977 and 0.902 in the training and test sets, respectively). The model's performance was further enhanced when combined with clinical variables. (The AUC values were 0.994 and 0.920, respectively.) Additionally, we found a close correlation between ITH score and heterogeneity, with statistically significant differences observed between high-risk and non-high-risk molecular subtypes. INTERPRETATION: The habitat model based on DKI is an ideal means for preoperatively predicting high-risk molecular subtypes of gliomas, holding significant value for noninvasively alerting malignant gliomas and those with malignant transformation potential.

Structural basis for activation of somatostatin receptor 5 by cyclic neuropeptide agonists.

Somatostatin receptor 5 (SSTR5) is an important G protein-coupled receptor and drug target for neuroendocrine tumors and pituitary disorders. This study presents two high-resolution cryogenicelectron microscope structures of the SSTR5-Gi complexes bound to the cyclic neuropeptide agonists, cortistatin-17 (CST17) and octreotide, with resolutions of 2.7 Å and 2.9 Å, respectively. The structures reveal that binding of these peptides causes rearrangement of a "hydrophobic lock", consisting of residues from transmembrane helices TM3 and TM6. This rearrangement triggers outward movement of TM6, enabling Gαi protein engagement and receptor activation. In addition to hydrophobic interactions, CST17 forms conserved polar contacts similar to somatostatin-14 binding to SSTR2, while further structural and functional analysis shows that extracellular loops differently recognize CST17 and octreotide. These insights elucidate agonist selectivity and activation mechanisms of SSTR5, providing valuable guidance for structure-based drug development targeting this therapeutically relevant receptor.

Molecular basis for the activation of PAF receptor by PAF.

Platelet-activating factor (PAF) is a potent phospholipid mediator crucial in multiple inflammatory and immune responses through binding and activating the PAF receptor (PAFR). However, drug development targeting the PAFR has been limited, partly due to an incomplete understanding of its activation mechanism. Here, we present a 2.9-Å structure of the PAF-bound PAFR-Gi complex. Structural and mutagenesis analyses unveil a specific binding mode of PAF, with the choline head forming cation-π interactions within PAFR hydrophobic pocket, while the alkyl tail penetrates deeply into an aromatic cleft between TM4 and TM5. Binding of PAF modulates conformational changes in key motifs of PAFR, triggering the outward movement of TM6, TM7, and helix 8 for G protein coupling. Molecular dynamics simulation suggests a membrane-side pathway for PAF entry into PAFR via the TM4-TM5 cavity. By providing molecular insights into PAFR signaling, this work contributes a foundation for developing therapeutic interventions targeting PAF signal axis.

The Controlled Preparation of a Carrier-Free Nanoparticulate Formulation Composed of Curcumin and Piperine Using High-Gravity Technology.

Carrier-free nanoparticulate formulations are an advantageous platform for the oral administration of insoluble drugs with the expectation of improving their bioavailability. However, the key limitation of exploiting carrier-free nanoparticulate formulations is the controlled preparation of drug nanoparticles on the basis of rational prescription design. In the following study, we used curcumin (Cur) and piperine (Pip) as model water-insoluble drugs and developed a new method for the controlled preparation of carrier-free drug nanoparticles via multidrug co-assembly in a high-gravity environment. Encouraged by the controlled regulation of the nucleation and crystal growth rate of high-gravity technology accomplished by a rotating packed bed, co-amorphous Cur-Pip co-assembled multidrug nanoparticles with a uniform particle size of 130 nm were successfully prepared, exhibiting significantly enhanced dissolution performance and in vitro cytotoxicity. Moreover, the hydrogen bonding interactions between Cur and Pip in nanoparticles provide them with excellent re-dispersibility and storage stability. Moreover, the oral bioavailability of Cur was dramatically enhanced as a result of the smaller particle size of the co-assembled nanoparticles and the effective metabolic inhibitory effect of Pip. The present study provides a controlled approach to preparing a carrier-free nanoparticulate formulation through a multidrug co-assembly process in the high-gravity field to improve the oral bioavailability of insoluble drugs.

CT-Based AI model for predicting therapeutic outcomes in ureteral stones after single extracorporeal shock wave lithotripsy through a cohort study.

OBJECTIVES: Exploring the efficacy of an artificial intelligence (AI) model derived from the analysis of CT images to precisely forecast the therapeutic outcomes of singular-session extracorporeal shock wave lithotripsy (ESWL) in the management of ureteral stones. METHODS: A total of 317 patients diagnosed clinically with ureteral stones were included in this investigation. Unenhanced CT was administered to the participants within the initial fortnight preceding the inaugural ESWL. The internal cohort consisted of 250 individuals from a local healthcare facility, whereas the external cohort comprised 67 participants from another local medical institution. The proposed framework comprises three main components: an automated semantic segmentation model developed using 3D U-Net, a feature extractor that integrates radiomics and autoencoder techniques, and an ESWL efficacy prediction model trained with various machine learning algorithms. All participants underwent thorough postoperative follow-up examinations four weeks hence. The efficacy of ESWL was defined by the absence of stones or residual fragments measuring ≤2 mm in KUB X-ray assessments. Model stability and generalizability were judiciously validated through a fivefold cross-validation approach and a multi-center external test strategy. Moreover, Shapley Additive Explanations (SHAP) values for individual features were computed to elucidate the nuanced contributions of each feature to the model's decision-making process. RESULTS: The semantic segmentation model we constructed exhibited an average Dice coefficient of 0.88 ± 0.08 on the external testing set. ESWL classifiers built using Support Vector Machine (SVM), Random Forest (RF), XGBoost (XB), and CatBoost (CB) achieved AUROC values of 0.78, 0.84, 0.85, and 0.90, respectively, on the internal validation set. For the external testing set, SVM, RF, XB, and CB predicted ESWL with AUROC values of 0.68, 0.79, 0.80, and 0.83, respectively, with the last one being the optimal algorithm. The radiomics features and auto-encoder features made significant contributions to the decision-making process of the classification model. CONCLUSIONS: This investigation unmistakably underscores the remarkable predictive prowess exhibited by a scrupulously crafted AI model using CT images to precisely anticipate the therapeutic results of a singular session of extracorporeal shock wave lithotripsy for ureteral stones.

Distinct characteristics of the gut virome in patients with osteoarthritis and gouty arthritis.

BACKGROUND/PURPOSE(S): The gut microbiota and its metabolites play crucial roles in pathogenesis of arthritis, highlighting gut microbiota as a promising avenue for modulating autoimmunity. However, the characterization of the gut virome in arthritis patients, including osteoarthritis (OA) and gouty arthritis (GA), requires further investigation. METHODS: We employed virus-like particle (VLP)-based metagenomic sequencing to analyze gut viral community in 20 OA patients, 26 GA patients, and 31 healthy controls, encompassing a total of 77 fecal samples. RESULTS: Our analysis generated 6819 vOTUs, with a considerable proportion of viral genomes differing from existing catalogs. The gut virome in OA and GA patients differed significantly from healthy controls, showing variations in diversity and viral family abundances. We identified 157 OA-associated and 94 GA-associated vOTUs, achieving high accuracy in patient-control discrimination with random forest models. OA-associated viruses were predicted to infect pro-inflammatory bacteria or bacteria associated with immunoglobulin A production, while GA-associated viruses were linked to Bacteroidaceae or Lachnospiraceae phages. Furthermore, several viral functional orthologs displayed significant differences in frequency between OA-enriched and GA-enriched vOTUs, suggesting potential functional roles of these viruses. Additionally, we trained classification models based on gut viral signatures to effectively discriminate OA or GA patients from healthy controls, yielding AUC values up to 0.97, indicating the clinical utility of the gut virome in diagnosing OA or GA. CONCLUSION: Our study highlights distinctive alterations in viral diversity and taxonomy within gut virome of OA and GA patients, offering insights into arthritis etiology and potential treatment and prevention strategies.

Discriminative analysis of schizophrenia and major depressive disorder using fNIRS.

BACKGROUND: Research into the shared and distinct brain dysfunctions in patients with schizophrenia (SCZ) and major depressive disorder (MDD) has been increasing. However, few studies have explored the application of functional near-infrared spectroscopy (fNIRS) in investigating brain dysfunction and enhancing diagnostic methodologies in these two conditions. METHODS: A general linear model was used for analysis of brain activation following task-state fNIRS from 131 patients with SCZ, 132 patients with MDD and 130 healthy controls (HCs). Subsequently, seventy-seven time-frequency analysis methods were used to construct new features of fNIRS, followed by the implementation of five machine learning algorithms to develop a differential diagnosis model for the three groups. This model was evaluated by comparing it to both a diagnostic model relying on traditional fNIRS features and assessments made by two psychiatrists. RESULTS: Brain activation analysis revealed significantly lower activation in Broca's area, the dorsolateral prefrontal cortex, and the middle temporal gyrus for both the SCZ and MDD groups compared to HCs. Additionally, the SCZ group exhibited notably lower activation in the superior temporal gyrus and the subcentral gyrus compared to the MDD group. When distinguishing among the three groups using independent validation datasets, the models utilizing new fNIRS features achieved an accuracy of 85.90 % (AUC = 0.95). In contrast, models based on traditional fNIRS features reached an accuracy of 52.56 % (AUC = 0.66). The accuracies of the two psychiatrists were 42.00 % (AUC = 0.60) and 38.00 % (AUC = 0.50), respectively. CONCLUSION: This investigation brings to light the shared and distinct neurobiological abnormalities present in SCZ and MDD, offering potential enhancements for extant diagnostic systems.

Spiral-Pipe Gas Anaerobic Digester.

The reduction of carbon dioxide to methane using hydrogen is an important process in biogas production. However, designing gas anaerobic digesters (GADs) based on this reaction presents several challenges. In this study, we developed an innovative spiral-pipe gas anaerobic digester (SGAD) to increase the displacement distance between the bubbles, thus prolonging the gas retention time and facilitating the reduction of CO2 to CH4 via H2. The process was successfully demonstrated by using a CO2/H2 ratio of 1:3 and a gas-feeding rate of 3.9 L Lr -1 d-1. During the experiment, more than 98% of the CO2 and 96% of the H2 were consumed, resulting in biogas containing ca. 86-96% CH4. Additionally, we applied our proposed evaluation methodology for assessing GAD performance to evaluate the performance of the SGAD. This methodology serves as a reference for evaluating and designing GAD systems. The innovative design of the SGAD and the corresponding evaluation methodology offer new insights into the design of reactors.

Regulatory mechanisms of plant rhizobacteria on plants to the adaptation of adverse agroclimatic variables.

The mutualistic plant rhizobacteria which improve plant development and productivity are known as plant growth-promoting rhizobacteria (PGPR). It is more significant due to their ability to help the plants in different ways. The main physiological responses, such as malondialdehyde, membrane stability index, relative leaf water content, photosynthetic leaf gas exchange, chlorophyll fluorescence efficiency of photosystem-II, and photosynthetic pigments are observed in plants during unfavorable environmental conditions. Plant rhizobacteria are one of the more crucial chemical messengers that mediate plant development in response to stressed conditions. The interaction of plant rhizobacteria with essential plant nutrition can enhance the agricultural sustainability of various plant genotypes or cultivars. Rhizobacterial inoculated plants induce biochemical variations resulting in increased stress resistance efficiency, defined as induced systemic resistance. Omic strategies revealed plant rhizobacteria inoculation caused the upregulation of stress-responsive genes-numerous recent approaches have been developed to protect plants from unfavorable environmental threats. The plant microbes and compounds they secrete constitute valuable biostimulants and play significant roles in regulating plant stress mechanisms. The present review summarized the recent developments in the functional characteristics and action mechanisms of plant rhizobacteria in sustaining the development and production of plants under unfavorable environmental conditions, with special attention on plant rhizobacteria-mediated physiological and molecular responses associated with stress-induced responses.

Effect of Polymer and Cell Membrane Coatings on Theranostic Applications of Nanoparticles: A Review.

The recent decade has witnessed a remarkable surge in the field of nanoparticles, from their synthesis, characterization, and functionalization to diverse applications. At the nanoscale, these particles exhibit distinct physicochemical properties compared to their bulk counterparts, enabling a multitude of applications spanning energy, catalysis, environmental remediation, biomedicine, and beyond. This review focuses on specific nanoparticle categories, including magnetic, gold, silver, and quantum dots (QDs), as well as hybrid variants, specifically tailored for biomedical applications. A comprehensive review and comparison of prevalent chemical, physical, and biological synthesis methods are presented. To enhance biocompatibility and colloidal stability, and facilitate surface modification and cargo/agent loading, nanoparticle surfaces are coated with different synthetic polymers and very recently, cell membrane coatings. The utilization of polymer- or cell membrane-coated nanoparticles opens a wide variety of biomedical applications such as magnetic resonance imaging (MRI), hyperthermia, photothermia, sample enrichment, bioassays, drug delivery, etc. With this review, the goal is to provide a comprehensive toolbox of insights into polymer or cell membrane-coated nanoparticles and their biomedical applications, while also addressing the challenges involved in translating such nanoparticles from laboratory benchtops to in vitro and in vivo applications. Furthermore, perspectives on future trends and developments in this rapidly evolving domain are provided.

Constructing High-order Functional Connectivity Networks with Temporal Information from fMRI Data.

Conducting functional connectivity analysis on functional magnetic resonance imaging (fMRI) data presents a significant and intricate challenge. Contemporary studies typically analyze fMRI data by constructing high-order functional connectivity networks (FCNs) due to their strong interpretability. However, these approaches often overlook temporal information, resulting in suboptimal accuracy. Temporal information plays a vital role in reflecting changes in blood oxygenation level-dependent signals. To address this shortcoming, we have devised a framework for extracting temporal dependencies from fMRI data and inferring high-order functional connectivity among regions of interest (ROIs). Our approach postulates that the current state can be determined by the FCN and the state at the previous time, effectively capturing temporal dependencies. Furthermore, we enhance FCN by incorporating high-order features through hypergraph-based manifold regularization. Our algorithm involves causal modeling of the dynamic brain system, and the obtained directed FC reveals differences in the flow of information under different pattern. We have validated the significance of integrating temporal information into FCN using four real-world fMRI datasets. On average, our framework achieves 12% higher accuracy than non-temporal hypergraph-based and low-order FCNs, all while maintaining a short processing time. Notably, our framework successfully identifies the most discriminative ROIs, aligning with previous research, thereby facilitating cognitive and behavioral studies.