The mediating effect of self-efficacy on family functioning and psychological resilience in prostate cancer patients.

Aims: Prostate cancer patients face impaired body image and psychological distress during the diagnosis and treatment of the disease, which leads to changes in mood, cognition and behavior. Psychological resilience has been shown to buffer shocks and stresses from the disease. Therefore, this study investigates the relationship between family functioning and psychological resilience in prostate cancer patients and the mediating role of self-efficacy between family functioning and psychological resilience to provide a relevant theoretical basis for improving patients' psychological status by providing relevant theoretical basis. Method: Using a cross-sectional design, participants were 215 patients with prostate cancer admitted to and treated in a tertiary hospital in Jiangsu province, China. Questionnaires were administered using the general information questionnaire, the Connor-Davidson Resilience Scale (CD-RISC), the Family Adaptation, Partnership, Growth, Affection, and Resolution Index (APGAR), and the General Self-efficacy Scale (GSES). Data were analyzed using descriptive and correlational analyses and the bootstrap mediation test was used to test the effect relationship between the variables. Results: Family functioning, self-efficacy and psychological resilience were significantly and positively correlated (r = 0.526, P < 0.01; r = 0.378, P < 0.01; r = 0.358, P < 0.01). The mediating effect of psychological resilience between family functioning and psychological resilience was significant, accounting for 42.56%. Conclusion: Family function and self-efficacy have been shown to increase the level of psychological resilience in prostate cancer patients. Attention should be paid to the mental health problems of prostate cancer patients, early screening and intervention, and the use of patients' family resources to improve their confidence in recovering from the disease, thus increasing their psychological resilience and improving their mental health.

The petroleum ether extracts of Chloranthus fortunei(A. Gray) Solms-Laub.with bioactivities: A rising source in HCC drug treatment.

ETHNOPHARMACOLOGICAL RELEVANCE: Hepatocellular Carcinoma (HCC) is an aggressive killer worldwide with high incidence and mortality. The herb Chloranthus fortunei (A. Gray) Solms-Laub is known as "Si Ji Feng" and is classified as a Feng-type medicine in classic Yao medicines. According to Yao's medical beliefs, Chloranthus fortunei has the functions of dispelling Feng, regulating qi, detoxifying, promoting blood circulation, etc. Folk uses its decoctions to treat stagnant liver conditions, such as liver abscesses, cirrhosis, hepatitis, and liver cancer. However, the bioactivity and mechanisms of Chloranthus fortunei extract against HCC have not been reported. AIM OF THE STUDY: To investigate the anti-HCC bioactivity and potential mechanism of the extract of Chloranthus fortunei (CFS). MATERIALS AND METHODS: Using 70% ethanol for reflux extraction of CFS resulted in the CFS ethanol extract, followed by sequential extractions with petroleum ether, chloroform, ethyl acetate, and n-butanol, yielding four fractions. The CCK-8 assay was utilized to examine the cytotoxic effects of 4 fractions on MHCC97-H and HepG2 cells, exploring the most effective component, namely petroleum ether extracts of CFS (PECFS). The major active ingredients of PECFS were identified using LC/MS technology, and the impact on cell proliferation and apoptosis in HCC cells was studied. The key genes and proteins in the pathway were validated using RT-PCR and Western blotting. BALB/c nude mice were chosen for tumor xenotransplantation and PECFS therapy. hinders the proliferation of HCC cells and promotes apoptosis. RESULTS: Among the four fractions, it was found that PECFS have the highest antiproliferative activity against MHCC97-H and HepG2 cells (IC50 = 13.86, 10.55 µg/mL), with sesquiterpene compounds being the primary active constituents. The antiproliferative activity of PECFS on HCC cells was linked to the inhibition of cell cloning, invasion, and metastasis abilities, as well as the arrest of the cell cycle at the G2/M phase. Additionally, exerts pro-apoptotic effects on HCC cells by upregulating the pro-apoptotic protein Bax, downregulating the anti-apoptotic protein Bcl-2, and activating the expression of the Caspase family. Moreover, protein and m-RNA expression data showed that PECFS inhibits HCC cell proliferation and promotes apoptosis by regulating the PI3K/AKT/mTOR pathway. Besides, after PECFS treatment, tumor growth in nude mice was suppressed. CONCLUSION: PECFS can inhibit the viability of HCC cells by acting on the PI3K/AKT/mTOR pathway, demonstrating anti-tumor potential. This study's findings suggest that PECFS may represent a promising source of novel agents for liver cancer treatment, providing scientific evidence for the traditional application of CFS in treating HCC.

An antibacterial, multifunctional nanogel for efficient treatment of neutrophilic asthma.

Asthma is a chronic and heterogeneous disease affecting the lungs and respiratory tract. In particular, the neutrophil subtype of asthma was described as persistent, more severe, and corticosteroid-resistant. Growing evidence suggested that nontypeable Haemophilus influenzae (NTHi) infection contributes to the development of neutrophilic asthma, exacerbating clinical symptoms and increasing the associated medical burden. In this work, arginine-grafted chitosan (CS-Arg) was ionically cross-linked with tris(2-carboxyethyl) phosphine (TCEP), and a highly-efficient antimicrobial agent, poly-ε-L-Lysine (ε-PLL), was incorporated to prepare ε-PLL/CS-Arg/TCEP (ECAT) composite nanogels. The results showed that ECAT nanogels exhibited highly effective inhibition against the proliferation of NTHi, Staphylococcus aureus (S. aureus) and Escherichia coli (E. coli). In addition, ECAT nanogels could effectively inhibit the formation of mucins aggregates in vitro, suggesting that the nanogel might have the potential to destroy mucin in respiratory disease. Furthermore, in the ovalbumin (OVA)/NTHi-induced Balb/c mice model of neutrophilic asthma, the number of neutrophils in the alveolar lavage fluid and the percentage of inflammatory cells in the blood were effectively reduced by exposure to tower nebulized administration of ECAT nanogels, and reversing airway hyperresponsiveness (AHR) and reducing inflammation in neutrophilic asthma mice. In conclusion, the construction of ECAT nanogels was a feasible anti-infective and anti-inflammatory therapeutic strategy, which demonstrated strong potential in the clinical treatment of neutrophilic asthma.

Factors influencing the job embeddedness of new graduate nurses: A multicentre cross-sectional study.

AIM: To identify factors associated with job embeddedness from the perspective of retaining new graduate nurses. DESIGN: The study was cross-sectional in design. METHODS: Convenience and stratified sampling were used to recruit 415 newly graduated nurses from 12 tertiary hospitals in China. Anonymized data were collected through self-designed sociodemographic questionnaires, job embeddedness scale, feedback-seeking behaviour scale, authentic leadership perception scale and decent work scale. Appropriate indicators were used for descriptive statistics and t-tests, ANOVA, Pearson correlation analysis and multiple linear regression to examine the influencing factors. RESULTS: The study showed that monthly income level, decent labour, authentic leadership and feedback-seeking behaviour were significant predictors of job embeddedness among new graduate nurses. CONCLUSION: The job embeddedness of new graduate nurses is moderate. Nursing managers need to construct reasonable and fair compensation incentives, adopt positive leadership styles and encourage proactive feedback-seeking behaviours to improve the job embeddedness of new graduate nurses and alleviate the nursing talent shortage. IMPACT: Exploring the factors influencing the job embeddedness of new graduate nurses provides a reference for establishing new graduate nurse retention strategies to help promote the career development of new graduate nurses and alleviate the nursing brain drain. REPORTING METHOD: We adhered to the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) guidelines. PATIENT OR PUBLIC CONTRIBUTION: No patient or public contribution.

Invasive metastatic tumor-camouflaged ROS responsive nanosystem for targeting therapeutic brain injury after cardiac arrest.

Drug transmission through the blood-brain barrier (BBB) is considered an arduous challenge for brain injury treatment following the return of spontaneous circulation after cardiac arrest (CA-ROSC). Inspired by the propensity of melanoma metastasis to the brain, B16F10 cell membranes are camouflaged on 2-methoxyestradiol (2ME2)-loaded reactive oxygen species (ROS)-triggered "Padlock" nanoparticles that are constructed by phenylboronic acid pinacol esters conjugated D-a-tocopheryl polyethylene glycol succinate (TPGS-PBAP). The biomimetic nanoparticles (BM@TP/2ME2) can be internalized, mainly mediated by the mutual recognition and interaction between CD44v6 expressed on B16F10 cell membranes and hyaluronic acid on cerebral vascular endothelial cells, and they responsively release 2ME2 by the oxidative stress microenvironment. Notably, BM@TP/2ME2 can scavenge excessive ROS to reestablish redox balance, reverse neuroinflammation, and restore autophagic flux in damaged neurons, eventually exerting a remarkable neuroprotective effect after CA-ROSC in vitro and in vivo. This biomimetic drug delivery system is a novel and promising strategy for the treatment of cerebral ischemia-reperfusion injury after CA-ROSC.

Metabolic surgery results in greater metabolic benefits in patients who achieve healthy weight.

BACKGROUND: A percentage of total weight loss (%TWL) >20% as the expected weight loss target after metabolic surgery might be insufficient to produce adequate metabolic benefits. OBJECTIVES: This study identified the optimal weight loss target to achieve substantial benefits from metabolic surgery. SETTING: University-affiliated tertiary care center. METHODS: In this retrospective study, participants were categorized into healthy weight (18.5 kg/m2 ≤ body mass index [BMI] < 24 kg/m2), overweight (24 kg/m2 ≤ BMI < 28 kg/m2), and obesity groups (BMI ≥28 kg/m2) according to their BMI 1 year after metabolic surgery. The weight loss and remission of obesity-related comorbidities were evaluated. Ordinal logistic regression analysis was used to identify predictors for achieving healthy weight 1 year postoperatively. RESULTS: Overall, 125 patients (112 sleeve gastrectomies, 13 Roux-en-Y gastric bypasses) were recruited in this study. Forty-two participants achieved healthy weight, 38 were overweight, and 45 had obesity. Type 2 diabetes mellitus and obstructive sleep apnea were relieved in all groups. Individuals who achieved healthy weight showed more improvements in nonalcoholic fatty liver disease, hypertension, and hyperuricemia than those who did not. Preoperative BMI was an independent predictor for the BMI achieved postoperatively, and the optimal cut-off point for achieving healthy weight was 34.9 kg/m2. CONCLUSIONS: Healthy weight was a more stringent target for patients who underwent metabolic surgery than the %TWL. Populations with a preoperative BMI of <34.9 kg/m2 were prone to realize the goal. Additional weight loss interventions could be considered for those with higher preoperative BMIs and enforced within 1 year postoperatively.

Interpretable deep learning insights: Unveiling the role of 1 Gy volume on lymphopenia after radiotherapy in breast cancer.

BACKGROUND: Lymphopenia is known for its significance on poor survivals in breast cancer patients. Considering full dosimetric data, this study aimed to develop and validate predictive models for lymphopenia after radiotherapy (RT) in breast cancer. MATERIAL AND METHODS: Patients with breast cancer treated with adjuvant RT were eligible in this multicenter study. The study endpoint was lympopenia, defined as the reduction in absolute lymphocytes and graded lymphopenia after RT. The dose-volume histogram (DVH) data of related critical structures and clinical factors were taken into account for the development of dense neural network (DNN) predictive models. The developed DNN models were validated using external patient cohorts. RESULTS: A total of 918 consecutive patients with invasive breast cancer enrolled. The training, testing, and external validating datasets consisted of 589, 203, and 126 patients, respectively. Treatment volumes at nearly all dose levels of the DVH were significant predictors for lymphopenia following RT, including volumes at very low-dose 1 Gy (V1) of organs at risk (OARs) including lung, heart and body, especially ipsilateral-lung V1. A final DNN model, combining full DVH dosimetric parameters of OARs and three key clinical factors, achieved a predictive accuracy of 75 % or higher. CONCLUSION: This study demonstrated and externally validated the significance of full dosimetric data, particularly the volume of low dose at as low as 1 Gy of critical structures on lymphopenia after radiation in patients with breast cancer. The significance of V1 deserves special attention, as modern VMAT RT technology often has a relatively high value of this parameter. Further study is warranted for RT plan optimization.

High-Dynamic-Range Integrated NV Magnetometers.

High-dynamic-range integrated magnetometers demonstrate extensive potential applications in fields involving complex and changing magnetic fields. Among them, Diamond Nitrogen Vacancy Color Core Magnetometer has outstanding performance in wide-range and high-precision magnetic field measurement based on its inherent high spatial resolution, high sensitivity and other characteristics. Therefore, an innovative frequency-tracking scheme is proposed in this study, which continuously monitors the resonant frequency shift of the NV color center induced by a time-varying magnetic field and feeds it back to the microwave source. This scheme successfully expands the dynamic range to 6.4 mT, approximately 34 times the intrinsic dynamic range of the diamond nitrogen-vacancy (NV) center. Additionally, it achieves efficient detection of rapidly changing magnetic field signals at a rate of 0.038 T/s.

Work-family conflict categories and support strategies for married female nurses: a latent profile analysis.

Objective: To clarify subgroups of married female nurses experiencing work-family conflict (WFC), explore the factors associated with the subgroups, and determine how desired support strategies differ among the subgroups. Methods: Data was collected from a sample of 646 married female nurses from public hospitals in Zhejiang Province, China, in December 2021. Latent profile analysis was used to group the participants, and multiple logistic regression was used to identify factors associated with higher WFC. The STROBE criteria were used to report results. Results: According to latent profile analysis, there were three distinct profiles of WFC among married female nurses: "low-conflict type," "work-dominant-conflict type," and "high-conflict type." These profiles differed in the number of children, night shifts, family economic burden, childcare during working hours, family harmony, colleague support, and nurse-patient relationships. Nurses with multiple children, higher pressures in childcare during working hours, heavier family economic burdens, lower family harmony, lower colleague support, and poorer nurse-patient relationships are more likely to be classified as "high-conflict type" nurses. Conclusion: This study found that married female nurses experience different types of WFCs. The structure of these WFCs and their associated factors suggests that customized intervention strategies can be developed to address the specific needs of married female nurses.

Football referee gesture recognition algorithm based on YOLOv8s.

Gesture serves as a crucial means of communication between individuals and between humans and machines. In football matches, referees communicate judgment information through gestures. Due to the diversity and complexity of referees' gestures and interference factors, such as the players, spectators, and camera angles, automated football referee gesture recognition (FRGR) has become a challenging task. The existing methods based on visual sensors often cannot provide a satisfactory performance. To tackle FRGR problems, we develop a deep learning model based on YOLOv8s. Three improving and optimizing strategies are integrated to solve these problems. First, a Global Attention Mechanism (GAM) is employed to direct the model's attention to the hand gestures and minimize the background interference. Second, a P2 detection head structure is integrated into the YOLOv8s model to enhance the accuracy of detecting smaller objects at a distance. Third, a new loss function based on the Minimum Point Distance Intersection over Union (MPDIoU) is used to effectively utilize anchor boxes with the same shape, but different sizes. Finally, experiments are executed on a dataset of six hand gestures among 1,200 images. The proposed method was compared with seven different existing models and 10 different optimization models. The proposed method achieves a precision rate of 89.3%, a recall rate of 88.9%, a mAP@0.5 rate of 89.9%, and a mAP@0.5:0.95 rate of 77.3%. These rates are approximately 1.4%, 2.0%, 1.1%, and 5.4% better than those of the newest YOLOv8s, respectively. The proposed method has right prospect in automated gesture recognition for football matches.

Simultaneous detection of multi-channel signals in MHz bandwidth using nitrogen-vacancy centers in a diamond.

In this paper, we propose a method for simultaneously recovering multiple radio wave signals based on nitrogen-vacancy (NV) centers in diamond combining optically detected magnetic resonance (ODMR) spectrum. A controlled magnetic field gradient applied to the laser excitation area on the surface of diamond widens the detectable ODMR bandwidth to 200 MHz. Three different frequency-modulated (FM) signals with distinct carrier frequencies falling within the resonance frequency range are received and demodulated in real-time. Subsequently, the FM signal reception capability of this system is further investigated by measuring baseband signal frequencies ranging from 0.1 Hz to 200 Hz and adjusting the carrier power within a dynamic range from -10 dBm to 30 dBm. This proposal, which accomplishes multi-channel demodulation using a compact and single device, has potential applications in fields such as wireless communication, radar and navigation.

Analysis of the Genomic Sequences and Metabolites of Bacillus velezensis YA215.

Discovering more novel antimicrobial compounds has become a keen research problem. In this study, YA215 genome was sequenced by the Illumina HiSeq + PacBio sequencing platform. Genome assembly was performed by Unicycler software and the gene clusters responsible for secondary metabolite biosynthesis were predicted by antiSMASH. The genome comprised 3976514 bp and had a 46.56% G + C content. 3809 coding DNA sequences, 27 rRNAs, 86 tRNAs genes, and 79 sRNA were predicted. Strain YA215 was re-identified as Bacillus velezensis based on ANI and OrthoANI analysis. In the COG database, 23 functional groups from 3090 annotations were predicted. In the GO database, 2654 annotations were predicted. 2486 KEGG annotations linked 41 metabolic pathways. Glycosyl transferases, polysaccharide lyases, auxiliary activities, glycoside hydrolases, carbohydrate esterases, and carbohydrate-binding modules were predicted among the 127 annotations in the CAZy database. AntiSMASH analysis predicted that B. velezensis YA215 boasted 13 gene clusters involved in synthesis of antimicrobial secondary metabolites including surfactin, fengycin, macrolactin H, bacillaene, difficidin, bacillibactin, bacilysin, and plantazolicin. Three of the gene clusters (gene cluster 5, gene cluster 9, and gene cluster 10) have the potential to synthesize unknown compounds. The research underscore the considerable potential of secondary metabolites, identified in the genomic composition of B. velezensis YA215, as versatile antibacterial agents with a broad spectrum of activity against pathogenic bacteria.

In vitro inhibitory effect of five natural sweeteners on α-glucosidase and α-amylase.

A promising and efficacious approach to manage diabetes is inhibiting α-glucosidase and α-amylase activity. Therefore, the inhibitory activities of five natural sweeteners (mogrosides (Mog), stevioside (Ste), glycyrrhizinic acid (GA), crude trilobatin (CT), and crude rubusoside (CR)) against α-glucosidase and α-amylase and their interactions were evaluated in vitro using enzyme kinetics, fluorescence spectroscopy, Fourier infrared spectroscopy, and molecular docking. The inhibitor sequence was CT > GA > Ste, as GA competitively inhibited α-glycosidase activity while CT and Ste exhibited mixed inhibitory effects. Compared to a positive control acarbose, the inhibitory activity of CT was higher. For α-amylase, the mixed inhibitors CT, CR, and Mog and the competitive inhibitor Ste effectively inhibited the enzyme, with the following order: CT > CR > Ste > Mog; nevertheless, the inhibitors were slightly inferior to acarbose. Three-dimensional fluorescence spectra depicted that GA, CT, and CR bound to the hydrophobic cavity of α-glucosidase or α-amylase and changed the polarity of the hydrophobic amino acid-based microenvironment and structure of the polypeptide chain backbone. Infrared spectroscopy revealed that GA, CT, and CR could disrupt the secondary structure of α-glucosidase or α-amylase, which decreased enzyme activity. GA, trilobatin and rubusoside bound to amino acid residues through hydrogen bonds and hydrophobic interactions, changing the conformation of enzyme molecules to decrease the enzymatic activity. Thus, CT, CR and GA exhibit promising inhibitory effects against α-glucosidase and α-amylase.

A retrospective study on the efficacy and safety of Envafolimab, a PD-L1 inhibitor, in the treatment of advanced malignant solid tumors.

Envafolimab, a PD-L1 inhibitor, has demonstrated potential in treating advanced malignant solid tumors (AMST). To study its' efficacy and safety in AMST, our retrospective study recruited 64 patients with various AMST, and treated with Envafolimab (400 mg every 3 weeks). We divided the patients into two cohorts: Cohort 1 (25 patients) receiving Envafolimab as first-line therapy, and Cohort 2 (39 patients) receiving it as second-line or subsequent therapy. Our analysis focused on Envafolimab's efficacy and safety. Over a median follow-up of 7.1 months, Cohort I reported a Disease Control Rate (DCR) of 72.0% and an Objective response rate (ORR) of 12.0%, while Cohort II had a DCR of 51.3% and an ORR of 5.1%. Notably, patients with more than four treatment cycles showed higher DCR and longer Progression-Free Survival (PFS) than those with fewer cycles. Adverse events were observed in 68.8% of patients, with severe events (CTCAE grade 3/4) in 14.1%. Most adverse events were mild, leading to treatment discontinuation in only 3.1% of patients, with no life-threatening events reported. In summary, Envafolimab is a safe and effective treatment for AMST, in both initial and later therapy stages, particularly with extended treatment duration, meriting further clinical trials.

Multi-cohort cerebrospinal fluid proteomics identifies robust molecular signatures for asymptomatic and symptomatic Alzheimer's disease.

Changes in Amyloid-ß (A), hyperphosphorylated Tau (T) in brain and cerebrospinal fluid (CSF) precedes AD symptoms, making CSF proteome a potential avenue to understand the pathophysiology and facilitate reliable diagnostics and therapies. Using the AT framework and a three-stage study design (discovery, replication, and meta-analysis), we identified 2,173 proteins dysregulated in AD, that were further validated in a third totally independent cohort. Machine learning was implemented to create and validate highly accurate and replicable (AUC>0.90) models that predict AD biomarker positivity and clinical status. These models can also identify people that will convert to AD and those AD cases with faster progression. The associated proteins cluster in four different protein pseudo-trajectories groups spanning the AD continuum and were enrichment in specific pathways including neuronal death, apoptosis and tau phosphorylation (early stages), microglia dysregulation and endolysosomal dysfuncton(mid-stages), brain plasticity and longevity (mid-stages) and late microglia-neuron crosstalk (late stages).

Markerless vision-based functional movement screening movements evaluation with deep neural networks.

The functional movement screen (FMS) test is a seven-test battery used to assess fundamental movement abilities of individuals. It is commonly used to predict sports injuries but relies on clinical expertise and is not suitable for self-examination. This study presents an automatic FMS movement assessment framework using a multi-view deep neural network called MVDNN. The framework combines automatic skeleton extraction with manual feature selection to extract 3D trajectory features of human skeleton joints from two different directions. Three mainstream methods of time-series modeling are then used to learn high-level feature representation from skeleton sequences, and motion features from two views are fused to provide complementary information. Results of public FMS movements dataset demonstrate that our MVDNN outperforms current state-of-the-art methods with an average miF1 score of 0.857, maF1 score of 0.768, and Kappa score of 0.640 over ten runs.

"Discovering shine through feedback seeking"---feedback seeking among new graduate nurses: a qualitative study.

BACKGROUND: Feedback is critical to improving practitioners' clinical practice and professional growth. Although they are still considered junior practitioners, their feedback-seeking experiences have yet to be investigated. This study aimed to understand the fundamental thoughts and experiences of new graduate nurses regarding feedback-seeking and to identify the main factors that influence their feedback-seeking behaviors. METHODS: Conducting a descriptive phenomenological study, semi-structured in-depth interviews with newly graduated nurses from four hospitals in Zhejiang Province, China, face-to-face or via video call in the hospital conference room through purposive and snowball sampling. Interview data were evaluated using Colaizzi's 7-step phenomenological data analysis. The COREQ checklist was followed. RESULTS: A total of 15 new graduate nurses were interviewed as a sample, and 13 categories emerged from our data. They were categorized into four central elements: (1) perceptions and attitudes, (2) drivers, (3) dilemmas and needs, and (4) transformation and growth. CONCLUSIONS: This study found that new graduate nurses have various needs but face dilemmas in the feedback-seeking process. Nursing managers should be proficient at providing positive leadership, collaborating with clinical mentors to foster an atmosphere where new graduate nurses may obtain honest, transparent, and fair feedback, and exercising caution when providing negative feedback.

Systematic proteomics in Autosomal dominant Alzheimer's disease reveals decades-early changes of CSF proteins in neuronal death, and immune pathways.

Background: To date, there is no high throughput proteomic study in the context of Autosomal Dominant Alzheimer's disease (ADAD). Here, we aimed to characterize early CSF proteome changes in ADAD and leverage them as potential biomarkers for disease monitoring and therapeutic strategies. Methods: We utilized Somascan® 7K assay to quantify protein levels in the CSF from 291 mutation carriers (MCs) and 185 non-carriers (NCs). We employed a multi-layer regression model to identify proteins with different pseudo-trajectories between MCs and NCs. We replicated the results using publicly available ADAD datasets as well as proteomic data from sporadic Alzheimer's disease (sAD). To biologically contextualize the results, we performed network and pathway enrichment analyses. Machine learning was applied to create and validate predictive models. Findings: We identified 125 proteins with significantly different pseudo-trajectories between MCs and NCs. Twelve proteins showed changes even before the traditional AD biomarkers (Aß42, tau, ptau). These 125 proteins belong to three different modules that are associated with age at onset: 1) early stage module associated with stress response, glutamate metabolism, and mitochondria damage; 2) the middle stage module, enriched in neuronal death and apoptosis; and 3) the presymptomatic stage module was characterized by changes in microglia, and cell-to-cell communication processes, indicating an attempt of rebuilding and establishing new connections to maintain functionality. Machine learning identified a subset of nine proteins that can differentiate MCs from NCs better than traditional AD biomarkers (AUC>0.89). Interpretation: Our findings comprehensively described early proteomic changes associated with ADAD and captured specific biological processes that happen in the early phases of the disease, fifteen to five years before clinical onset. We identified a small subset of proteins with the potentials to become therapy-monitoring biomarkers of ADAD MCs. Funding: Proteomic data generation was supported by NIH: RF1AG044546.

Effects of the promoting bacterium on growth of plant under cadmium stress.

Cadmium (Cd) pollution is a huge threat to ecosystem health. In the manuscript, pot experiments were conducted to investigate the changes in plant biomass and antioxidant indicators under different cadmium pollution levels (0, 25, 50, and 100 mg/kg) of inoculation of plant growth-promoting bacteria ZG7 on sugar beet. The results showed that the accumulation of excess Cd in sugar beet exhibited different symptoms, including reduced biomass (p < 0.05). Compared with the group treated with uninoculated strain ZG7, inoculation of strain ZG7 significantly reduced the toxicity of sugar beet to Cd and enhanced its antioxidant capacity, with no significant differences in root biomass and increases in leaf biomass of 15.71, 5.84, and 74.12 under different Cd concentration treatments (25, 50, and 100 mg/kg), respectively. The root enrichment of Cd was reduced by 49.13, 47.26, and 21.50%, respectively (p < 0.05). The leaf fraction was reduced by 59.35, 29.86, and 30.99%, respectively (p < 0.05). In addition, the enzymatic activities of sucrase, urease, catalase, and neutral phosphatase were significantly enhanced in the soil (p < 0.05). This study helps us to further investigate the mechanism of cadmium toxicity reduction by inoculated microorganisms and provides a theoretical reference for growing plants in cadmium-contaminated agricultural fields.

The combination of microorganisms and phytoremediation is becoming a popular research topic. The selection of suitable plant growth promoting bacteria can not only promote the growth and development of plants and enhance their cadmium resistance, but also improve the soil quality. And the results of this study will be important for growing edible plants and improving soils in cadmium-contaminated areas.

Mitigation of Anti-Drug Antibody Production for Augmenting Anticancer Efficacy of Therapeutic Protein via Co-Injection of Nano-Rapamycin.

The induction of anti-drug antibody (ADA) is a formidable challenge for protein-based therapy. Trichosanthin (TCS) as a class of ribosome-inactivating proteins is widely studied in tumor treatment. However, the immunogenicity can induce the formation of ADA, which can cause hypersensitivity reactions and neutralize the efficacy of TCS, thus limiting its clinical application in cancer therapy. Here, a promising solution to this issue is presented by co-administration of the rapamycin nanoparticles and TCS. PEGylated rapamycin amphiphilic molecule is designed and synthesized as a prodrug and a delivery carrier, which can self-assemble into a nanoparticle system with encapsulation of free rapamycin, a hydrophobic drug. It is found that co-injection of the PEGylated rapamycin nanoparticles and TCS could mitigate the formation of anti-TCS antibody via inducing durable immunological tolerance. Importantly, the combination of TCS and the rapamycin nanoparticles has an enhanced effect on inhibit the growth of breast cancer. This work provides a promising approach for protein toxin-based anticancer therapy and for promoting the clinical translation.