Screening and validation of atherosclerosis PAN-apoptotic immune-related genes based on single-cell sequencing.

Background: Carotid atherosclerosis (CAS) is a complication of atherosclerosis (AS). PAN-optosome is an inflammatory programmed cell death pathway event regulated by the PAN-optosome complex. CAS's PAN-optosome-related genes (PORGs) have yet to be studied. Hence, screening the PAN-optosome-related diagnostic genes for treating CAS was vital. Methods: We introduced transcriptome data to screen out differentially expressed genes (DEGs) in CAS. Subsequently, WGCNA analysis was utilized to mine module genes about PANoptosis score. We performed differential expression analysis (CAS samples vs. standard samples) to obtain CAS-related differentially expressed genes at the single-cell level. Venn diagram was executed to identify PAN-optosome-related differential genes (POR-DEGs) associated with CAS. Further, LASSO regression and RF algorithm were implemented to were executed to build a diagnostic model. We additionally performed immune infiltration and gene set enrichment analysis (GSEA) based on diagnostic genes. We verified the accuracy of the model genes by single-cell nuclear sequencing and RT-qPCR validation of clinical samples, as well as in vitro cellular experiments. Results: We identified 785 DEGs associated with CAS. Then, 4296 module genes about PANoptosis score were obtained. We obtained the 7365 and 1631 CAS-related DEGs at the single-cell level, respectively. 67 POR-DEGs were retained Venn diagram. Subsequently, 4 PAN-optosome-related diagnostic genes (CNTN4, FILIP1, PHGDH, and TFPI2) were identified via machine learning. Cellular function tests on four genes showed that these genes have essential roles in maintaining arterial cell viability and resisting cellular senescence. Conclusion: We obtained four PANoptosis-related diagnostic genes (CNTN4, FILIP1, PHGDH, and TFPI2) associated with CAS, laying a theoretical foundation for treating CAS.

Intermittent sliding-lock-knot suture for limbal conjunctival autograft fixation in pterygium surgery: a technique note.

AIM: To report a technique used with intermittent sliding-lock-knot (ISLK) fixation for limbal conjunctival autografts in pterygium surgery and compared with those of routine intermittent (RI) fixation. METHODS: Consecutive patients with primary pterygium who had undergone pterygium excision combined with limbal conjunctival autograft transplantation between March 2021 and March 2022 at our institute were retrospectively analyzed. Primary outcome measures were mean duration of surgery and suture removal, degree of conjunctival hyperemia on postoperative day 1, pain score at suture removal, postoperative symptoms at 6mo, including conjunctival hyperemia, foreign body sensation, and graft stability. RESULTS: Ninety-eight patients underwent monocular surgery and were divided into ISLK (51 eyes) and RI (47 eyes) groups according to the type of conjunctiva autograft fixation method planned. There was no significant difference in mean duration of surgery between the two groups (18.59±2.39min vs 18.15±2.20min, P=0.417); however, compared to the RI group, shorter suture removal times were observed in the ISLK group [0.58min (0.42-0.87) vs 3.00min (2.21-4.15), P<0.001]. The degree of conjunctival hyperemia on postoperative day 1 was milder in the ISLK group (P<0.001). Pain scores at suture removal were lower in the ISLK group than in RI group [1 (0-3) vs 2 (1-4), P<0.001]. Postoperative symptoms at 6mo were comparable between the groups (P=0.487), with no recurrence. CONCLUSION: ISLK is an innovative method for limbal conjunctival autograft fixation after pterygium excision. Compared to RI fixation, ISLK facilitates suture removal and reduces discomfort, with comparable surgery duration and less conjunctival hyperemia.

Domiciliary monitoring of exhaled nitric oxide in the management of asthma: a pilot study.

BACKGROUND: Whether asthma patients could benefit from home monitoring for fractional exhaled nitric oxide (flow of 50 mL/s, FeNO50) is unknown. We explore the application value of home monitoring FeNO50 in daily asthma management. METHODS: Twenty-two untreated, uncontrolled asthma patients were selected. Medical history, blood and sputum samples, pulmonary function, Asthma Control Test (ACT), and other clinical data of the subjects were collected. All subjects underwent daily monitoring for four weeks using a FeNO50 monitor and mobile spirometry (mSpirometry). The diurnal differences and dynamic changes were described. Compare the effect-acting time and the relative plateau of treatment between FeNO50 and mSpirometry monitoring. RESULTS: In the first two weeks, the morning median (IQR) level of FeNO50 was 44 (35, 56) ppb, which was significantly higher than the evening median level [41 (32, 53) ppb, P = 0.028]. The median (IQR) effect-acting time assessed by FeNO50 was 4 (3, 5) days, which was significantly earlier than each measure of mSpirometry (P < 0.05). FeNO50 reached the relative plateau significantly earlier than FEV1 (15 ± 2 days vs. 21 ± 3 days, P < 0.001). After treatment, the daily and weekly variation rates of FeNO50 showed a gradually decreasing trend (P < 0.05). The ACT score, sputum eosinophils, and blood eosinophils also significantly improved (P ≤ 0.01). CONCLUSIONS: The daily home monitoring of FeNO50 in asthmatic patients showed significant circadian rhythm, and the sensitivity of FeNO50 in evaluating the response to treatment was higher than mSpirometry. The daily and weekly variation rates of FeNO50 change dynamically with time, which may be used to assess the condition of asthma.

Decoding the DSCC1 gene as a pan-cancer biomarker in human cancers via comprehensive multi-omics analyses.

OBJECTIVES: While dysregulation of DSCC1 (DNA Replication And Sister Chromatid Cohesion 1) has been established in breast cancer and colorectal cancer, its associations with other tumors remain unclear. Therefore, this study was launched to explore the role of DSCC1 in pan-cancer. METHODOLOGY: In this study, we investigate the biological functions of DSCC1 across 33 solid tumors, elucidating its role in promoting oncogenesis and progression in various cancers through comprehensive analysis of multi-omics data. RESULTS: We conducted a comprehensive analysis of DSCC1 expression using RNA-seq data from TCGA and GTEx databases across 30 cancer types. Striking variations were observed, with significant overexpression of DSCC1 identified in numerous cancers. Elevated DSCC1 level was strongly associated with poorer prognosis, shorter survival, and advanced tumor stages in kidney renal papillary cell carcinoma (KIRP), liver hepatocellular carcinoma (LIHC), lung adenocarcinoma (LUAD), as indicated by Kaplan-Meier curves and GEPIA2 analysis. Further investigation into the molecular mechanisms revealed reduced DNA methylation in the DSCC1 promoter region in KIRP, LIHC, and LUAD, supporting enhanced RNA transcription. Protein expression analysis via the Human Protein Atlas (HPA) corroborated mRNA expression findings, showcasing elevated DSCC1 protein in KIRP, LIHC, and LUAD tissues. Mutational analysis using cBioPortal revealed alterations in 0.4% of KIRP, 17% of LIHC, and 5% of LUAD samples, predominantly characterized by amplification. Immune cell infiltration analysis demonstrated robust positive correlations between DSCC1 expression and CD8+ T cells, CD4+ T cells, and B cells, influencing the tumor microenvironment. STRING and gene enrichment analyses unveiled DSCC1's involvement in critical pathways, emphasizing its multifaceted impact. Notably, drug sensitivity analysis highlighted a significant correlation between DSCC1 mRNA expression and responses to 78 anticancer treatments, suggesting its potential as a predictive biomarker and therapeutic target for KIRP, LIHC, and LUAD. Finally, immunohistochemistry staining of clinical samples validated computational results, confirming elevated DSCC1 protein expression. CONCLUSION: Overall, this study provides comprehensive insights into the pivotal role of DSCC1 in KIRP, LIHC, and LUAD initiation, progression, and therapeutic responsiveness, laying the foundation for further investigations and personalized treatment strategies.

Biogenesis of Rab14-positive endosome buds at Golgi-endosome contacts by the RhoBTB3-SHIP164-Vps26B complex.

Early endosomes (EEs) are crucial in cargo sorting within vesicular trafficking. While cargoes destined for degradation are retained in EEs and eventually transported to lysosomes, recycled cargoes for the plasma membrane (PM) or the Golgi undergo segregation into specialized membrane structures known as EE buds during cargo sorting. Despite this significance, the molecular basis of the membrane expansion during EE bud formation has been poorly understood. In this study, we identify a protein complex comprising SHIP164, an ATPase RhoBTB3, and a retromer subunit Vps26B, which promotes the formation of EE buds at Golgi-EE contacts. Our findings reveal that Vps26B acts as a novel Rab14 effector, and Rab14 activity regulates the association of SHIP164 with EEs. Depletion of SHIP164 leads to enlarged Rab14+ EEs without buds, a phenotype rescued by wild-type SHIP164 but not the lipid transfer-defective mutants. Suppression of RhoBTB3 or Vps26B mirrors the effects of SHIP164 depletion. Together, we propose a lipid transport-dependent pathway mediated by the RhoBTB3-SHIP164-Vps26B complex at Golgi-EE contacts, which is essential for EE budding.

Analysis of the mediating effect between ehealth literacy and health self-management of undergraduate nursing students' mental health literacy.

BACKGROUND: Good health self-management positively affects the health of healthcare providers and their ability to manage their patients' health. This study explored the relationship between ehealth literacy, health self-management skills, and mental health literacy among undergraduate nursing students. Some studies have confirmed the correlation between e-health literacy and health self-management skills, while mental health literacy may be correlated with both, and this study aims to explore the relationship between the three. METHODS: A descriptive cross-sectional survey was conducted at a medical university in northwestern China among 385 Chinese undergraduate nursing students. Participants completed the General Information Questionnaire, the Adult Health Self-Management Skills Rating Scale, the Mental Health Literacy Rating Scale, and the eHealth Literacy Scale, and provided valid responses. The IBM SPSS 27.0 statistical software was used for data entry and descriptive analysis, t-test, ANOVA, and Pearson correlation analysis. The IBM Amos 26.0 was used to construct the mediation effect model, and the Bootstrap method was employed to test mediating effects. RESULTS: Mental health literacy, ehealth literacy, and health self-management skills of undergraduate nursing students were at a moderate to high level. Mental health literacy, ehealth literacy, and health self-management were positively correlated. Mental health literacy, particularly, played a partial mediating role of 31.1% ( 95% CI [0.307-1.418] ) between ehealth literacy and health self-management. CONCLUSIONS: Undergraduate nursing students' mental health literacy partially mediates the link between eHealth literacy and health self-management skills. Schools should emphasize the development of nursing students' e-health literacy and mental health literacy in order to improve their health self-management skills, which will not only bring about a better health outcome for the students, but will also benefit the health of the social population.

Association of follow-up neutrophil-to-lymphocyte ratio and systemic inflammation response index with stroke-associated pneumonia and functional outcomes in cerebral hemorrhage patients: a case controlled study.

BACKGROUND: Neutrophil-to-lymphocyte ratio (NLR) and systemic inflammation response index (SIRI) at admission are independent diagnostic biomarkers in stroke-associated pneumonia (SAP). Our study aimed to investigate the association between NLR, SIRI, specifically follow-up NLR and SIRI, and SAP, as well as their relationship with functional outcomes. MATERIALS AND METHODS: We retrospectively included 451 consecutive ICH patients from May 2017 to May 2019. We conducted univariate and multivariable analyses to identify the factors independently associated with SAP and poor functional outcomes. RESULTS: Compared to 127 (28.16%) patients diagnosed with SAP, those without SAP had both lower baseline and follow-up NLR and SIRI values (P<0.001). After adjustments, we found that baseline NLR (OR, 1.039 [95% CI, 1.003-1.077]; P=0.036) and follow-up NLR (OR, 1.054 [95% CI, 1.011-1.098]; P=0.012) were independently associated with SAP. The follow-up NLR was also associated with a higher mRS (OR, 1.124 [95% CI, 1.025-1.233]; P=0.013) and lower ADL-MBI score (OR, 1.167 [95% CI, 1.057-1.289]; P=0.002) at discharge. Multivariable analysis indicated that advanced age and nasogastric tube feeding were independently associated with SAP (P<0.05). We constructed a dynamic nomogram to identify SAP risk. Further subgroup analysis revealed that baseline NLR (OR, 1.062 [95% CI, 1.007-1.120]; P=0.026) is independently associated with SAP in the nasogastric feeding group, while follow-up NLR (OR, 1.080 [95% CI, 1.024-1.139]; P=0.005) was associated with the occurrence of SAP in non-nasogastric feeding patients. CONCLUSIONS: We found elevated baseline and follow-up NLR values were associated with SAP occurrence, and increasing follow-up NLR indicated poor functional outcomes. Inflammatory markers at different stages may offer individualized guidance for patients receiving various treatments.

Multiparametric MRI-Based Interpretable Radiomics Machine Learning Model Differentiates Medulloblastoma and Ependymoma in Children: A Two-Center Study.

RATIONALE AND OBJECTIVES: Medulloblastoma (MB) and Ependymoma (EM) in children, share similarities in age group, tumor location, and clinical presentation. Distinguishing between them through clinical diagnosis is challenging. This study aims to explore the effectiveness of using radiomics and machine learning on multiparametric magnetic resonance imaging (MRI) to differentiate between MB and EM and validate its diagnostic ability with an external set. MATERIALS AND METHODS: Axial T2 weighted image (T2WI) and contrast-enhanced T1weighted image (CE-T1WI) MRI sequences of 135 patients from two centers were collected as train/test sets. Volume of interest (VOI) was manually delineated by an experienced neuroradiologist, supervised by a senior. Feature selection analysis and the least absolute shrinkage and selection operator (LASSO) algorithm identified valuable features, and Shapley additive explanations (SHAP) evaluated their significance. Five machine-learning classifiers-extreme gradient boosting (XGBoost), Bernoulli naive Bayes (Bernoulli NB), Logistic Regression (LR), support vector machine (SVM), linear support vector machine (Linear SVC) classifiers were built based on T2WI (T2 model), CE-T1WI (T1 model), and T1 + T2WI (T1 + T2 model). A human expert diagnosis was developed and corrected by senior radiologists. External validation was performed at Sun Yat-Sen University Cancer Center. RESULTS: 31 valuable features were extracted from T2WI and CE-T1WI. XGBoost demonstrated the highest performance with an area under the curve (AUC) of 0.92 on the test set and maintained an AUC of 0.80 during external validation. For the T1 model, XGBoost achieved the highest AUC of 0.85 on the test set and the highest accuracy of 0.71 on the external validation set. In the T2 model, XGBoost achieved the highest AUC of 0.86 on the test set and the highest accuracy of 0.82 on the external validation set. The human expert diagnosis had an AUC of 0.66 on the test set and 0.69 on the external validation set. The integrated T1 + T2 model achieved an AUC of 0.92 on the test set, 0.80 on the external validation set, achieved the best performance. Overall, XGBoost consistently outperformed in different classification models. CONCLUSION: The combination of radiomics and machine learning on multiparametric MRI effectively distinguishes between MB and EM in childhood, surpassing human expert diagnosis in training and testing sets.

Nitrogen addition affected the root competition in Cunninghamia lanceolata-Phoebe chekiangensis mixed plantation.

Little is known about below-ground competition in mixed-species plantations under increasing nitrogen (N) deposition. This study aims to determine the effects of N addition on root competition in coniferous and broad-leaved species mixed plantations. A pot experiment was conducted using the coniferous species Cunninghamia lanceolata and the broad-leaved species Phoebe chekiangensis planted in mixed plantations with different competition intensities under N addition (0 or 45 kg N ha-1 yr-1). Biomass allocation, root morphology, root growth level, and competitive ability were determined after five months of treatment. Our findings indicated that root interactions in mixed plantations did not influence biomass allocation in either C. lanceolata or P. chekiangensis but promoted growth in C. lanceolata when no N was added. However, N addition decreased biomass accumulation in both species in the mixed plantation and had a negative effect on the root growth of C. lanceolata due to intensified competition. Addition of N increased the relative importance of root predatory competition in P. chekiangensis, and increased the allelopathic competitive advantage in C. lanceolata. This suggests that N addition causes a shift in the root competitive strategy from tolerance to competition. Overall, these findings highlight the significant impact that the addition of N can have on plant interactions in mixed plantations. Our results provide implications for the mechanisms of root competition in response to increasing atmospheric N deposition in mixed plantations.

Heterologous Biosynthesis of Kauralexin A1 in Saccharomyces cerevisiae through Metabolic and Enzyme Engineering.

Kauralexin A1 (KA1) is a key intermediate of the kauralexin A series metabolites of maize phytoalexins. However, their application is severely limited by their low abundance in maize. In this study, an efficient biosynthetic pathway was constructed to produce KA1 in Saccharomyces cerevisiae. Also, metabolic and enzyme engineering strategies were applied to construct the high-titer strains, such as chassis modification, screening synthases, the colocalization of enzymes, and multiple genomic integrations. First, the KA1 precursor ent-kaurene was synthesized using the efficient diterpene synthase GfCPS/KS from Fusarium fujikuroi, and optimized to reach 244.36 mg/L in shake flasks, which displayed a 200-fold increase compared to the initial strain. Then, the KA1 was produced under the catalysis of ZmCYP71Z18 from Zea mays and SmCPR1 from Salvia miltiorrhiza, and the titer was further improved by integrating the fusion protein into the genome. Finally, an ent-kaurene titer of 763.23 mg/L and a KA1 titer of 42.22 mg/L were achieved through a single-stage fed-batch fermentation in a 5 L bioreactor. This is the first report of the heterologous biosynthesis of maize diterpene phytoalexins in S. cerevisiae, which lays a foundation for further pathway reconstruction and biosynthesis of the kauralexin A series maize phytoalexins.

Anaplastic Lymphoma Kinase (ALK) Inhibitors Show Activity in Colorectal Cancer With ALK Rearrangements: Case Series and Literature Review.

Anaplastic lymphoma kinase (ALK) rearrangement is a well-known driver oncogene detected in approximately 5% of non-small cell lung cancer. However, ALK rearrangement is much less frequent in other solid tumors outside the lungs, such as colorectal cancer (CRC); thus, the optimal management of CRC with ALK rearrangements has yet to be established. In this report, we describe 2 cases of ALK-positive CRC, both of which benefited from ALK tyrosine kinase inhibitor (ALK-TKI) therapy. Case 1 was a postoperative patient with poorly differentiated colon adenocarcinoma, who was diagnosed with metastatic relapse shortly after surgery. Both fluorouracil, leucovorin, and oxaliplatin (FOLFOX) and bevacizumab combined with 5-fluorouracil, l-leucovorin, and irinotecan (FOLFIRI) proved ineffective against the disease. The patient was then treated with ensartinib, as the CAD-ALK fusion gene was detected by genomic analysis. The patient was initially treated with ensartinib monotherapy for 9 months, then with ensartinib combined with local radiotherapy and fruquintinib for another 4 months for isolated hilar hepatic lymph node metastasis. The patient experienced disease progression with an acquired ALK G1202R resistance mutation that responded well to lorlatinib. Case 2 involved a 72-year-old man with advanced colon cancer (pT4bN2aM1b, stage IV) harboring an EML4-ALK fusion. The patient underwent resection of the right colon tumor due to intestinal obstruction, but the disease continued to progress after 12 courses of FOLFIRI and bevacizumab chemotherapy. However, the patient responded remarkably well to alectinib. Our report emphasizes the importance of gene detection in the treatment of malignant tumors, and the significance of ALK mutations in CRC.

Multifunctional ZnO@DOX/ICG-LMHP Nanoparticles for Synergistic Multimodal Antitumor Activity.

Multifunctional nanoparticles are of significant importance for synergistic multimodal antitumor activity. Herein, zinc oxide (ZnO) was used as pH-sensitive nanoparticles for loading the chemotherapy agent doxorubicin (DOX) and the photosensitizer agent indocyanine green (ICG), and biocompatible low-molecular-weight heparin (LMHP) was used as the gatekeepers for synergistic photothermal therapy/photodynamic therapy/chemotherapy/immunotherapy. ZnO was decomposed into cytotoxic Zn2+ ions, leading to a tumor-specific release of ICG and DOX. ZnO simultaneously produced oxygen (O2) and reactive oxygen species (ROS) for photodynamic therapy (PDT). The released ICG under laser irradiation produced ROS for PDT and raised the tumor temperature for photothermal therapy (PTT). The released DOX directly caused tumor cell death for chemotherapy. Both DOX and ICG also induced immunogenic cell death (ICD) for immunotherapy. The in vivo and in vitro results presented a superior inhibition of tumor progression, metastasis and recurrence. Therefore, this study could provide an efficient approach for designing multifunctional nanoparticles for synergistic multimodal antitumor therapy.

Physically Unclonable Holographic Encryption and Anticounterfeiting Based on the Light Propagation of Complex Medium and Fluorescent Labels.

Physically unclonable function (PUF) methods have high security, but their wide application is limited by complex encoding, large database, advanced external characterization equipment, and complicated comparative authentication. Therefore, we creatively propose the physically unclonable holographic encryption and anticounterfeiting based on the light propagation of complex medium and fluorescent labels. As far as we know, this is the first holographic encryption and anticounterfeiting method with a fluorescence physically unclonable property. The proposed method reduces the above requirements of traditional PUF methods and significantly reduces the cost. The angle-multiplexed PUF fluorescent label is the physical secret key. The information is encrypted as computer-generated holograms (CGH). Many physical parameters in the system are used as the parameter secret keys. The Diffie-Hellman key exchange algorithm is improved to transfer parameter secret keys. A variety of complex medium hologram generation methods are proposed and compared. The effectiveness, security, and robustness of the method are studied and analyzed. Finally, a graphical user interface (GUI) is designed for the convenience of users. The advantages of this method include lower PUF encoding complexity, effective reduction of the database size, lower requirements for characterization equipment, and direct use of decrypted information without complicated comparative authentication to reduce misjudgment. It is believed that the method proposed in this paper will pave the way for the popularization and application of PUF-based anticounterfeiting and encryption methods.

Disease trajectory of high neuroticism and the relevance to psychiatric disorders: A retro-prospective cohort study.

BACKGROUND: Neuroticism is a psychological personality trait that has a significant impact on public health and is also a potential predisposing factor for adverse disease outcomes; however, comprehensive studies of the subsequently developed conditions are lacking. The starting point of disease trajectory in terms of genetic variation remains unclear. METHOD: Our study included 344,609 adult participants from the UK Biobank cohort who were virtually followed up from January 1, 1997. Neuroticism levels were assessed using 12 items from the Eysenck Personality Questionnaire. We performed a phenome-wide association analysis of neuroticism and subsequent diseases. Binomial tests and logistic regression models were used to test the temporal directionality and association between disease pairs to construct disease trajectories. We also investigated the association between polygenic risk scores (PRSs) for five psychiatric traits and high neuroticism. RESULTS: The risk for 59 diseases was significantly associated with high neuroticism. Depression, anxiety, irritable bowel syndrome, migraine, spondylosis, and sleep disorders were the most likely to develop, with hazard ratios of 6.13, 3.66, 2.28, 1.74, 1.74, and 1.71, respectively. The disease trajectory network revealed two major disease clusters: cardiometabolic and chronic inflammatory diseases. Medium/high genetic risk groups stratified by the PRSs of four psychiatric traits were associated with an elevated risk of high neuroticism. We further identified eight complete phenotypic trajectory clusters of medium or high genetic risk for psychotic, anxiety-, depression-, and stress-related disorders. CONCLUSION: Neuroticism plays an important role in the development of somatic and mental disorders. The full picture of disease trajectories from the genetic risk of psychiatric traits and neuroticism in early life to a series of diseases later provides evidence for future research to explore the etiological mechanisms and precision management.

New targets of TetR-type regulator SLCG_2919 for controlling lincomycin biosynthesis in Streptomyces lincolnensis.

The transcription factor (TF)-mediated regulatory network controlling lincomycin production in Streptomyces lincolnensis is yet to be fully elucidated despite several types of associated TFs having been reported. SLCG_2919, a tetracycline repressor (TetR)-type regulator, was the first TF to be characterized outside the lincomycin biosynthetic cluster to directly suppress the lincomycin biosynthesis in S. lincolnensis. In this study, improved genomic systematic evolution of ligands by exponential enrichment (gSELEX), an in vitro technique, was adopted to capture additional SLCG_2919-targeted sequences harboring the promoter regions of SLCG_6675, SLCG_4123-4124, SLCG_6579, and SLCG_0139-0140. The four DNA fragments were confirmed by electrophoretic mobility shift assays (EMSAs). Reverse-transcription quantitative polymerase chain reaction (RT-qPCR) showed that the corresponding target genes SLCG_6675 (anthranilate synthase), SLCG_0139 (LysR family transcriptional regulator), SLCG_0140 (beta-lactamase), SLCG_6579 (cytochrome P450), SLCG_4123 (bifunctional DNA primase/polymerase), and SLCG_4124 (magnesium or magnesium-dependent protein phosphatase) in ΔSLCGL_2919 were differentially increased by 3.3-, 4.2-, 3.2-, 2.5-, 4.6-, and 2.2-fold relative to those in the parental strain S. lincolnensis LCGL. Furthermore, the individual inactivation of these target genes in LCGL reduced the lincomycin yield to varying degrees. This investigation expands on the known DNA targets of SLCG_2919 to control lincomycin production and lays the foundation for improving industrial lincomycin yields via genetic engineering of this regulatory network.

A novel strategy for specific sensing and inactivation of Escherichia coli: Constructing a targeted sandwich-type biosensor with multiple SERS hotspots to enhance SERS detection sensitivity and near-infrared light-triggered photothermal sterilization performance.

Human health is greatly threatened by bacterial infection, which raises the risk of serious illness and death in humans. For early screening and accurate treatment of bacterial infection, there is a strong desire to undertake ultrasensitive detection and effective killing of pathogenic bacteria. Herein, a novel surface-enhanced Raman scattering (SERS) biosensor based on sandwich structure consisting of capture probes/bacteria/SERS tags was established for specific identification, capture and photothermal killing of Escherichia coli (E. coli). Finite-difference time-domain (FDTD) technique was used to simulate the electromagnetic field distribution of capture probes, SERS tags and sandwich-type SERS substrate, and a possible SERS enhancement mechanism based on sandwich structure was presented and discussed. Sandwich-type SERS biosensor successfully achieved distinctive identification and magnetic beneficiation of E. coli. In addition, a single SERS substrate, including capture probes and SERS tags, could also achieve outstanding photothermal effects as a consequence of localized surface plasmon resonance (LSPR) effect. Intriguingly, sandwich-type SERS biosensor demonstrated a higher photothermal conversion efficiency (50.03 %) than the single substrate, which might be attributed to the formation of target bacterial clusters. The superior biocompatibility and the low toxicity of the sandwich-type biosensor were confirmed. Our approach offers a fresh method for constructing sandwich-type biosensor with multiple SERS hotspots based on extremely effective hybrid plasmonic nanoparticles, and has a wide range of potential applications in the recognition and treatment of bacteria.

Adipose-derived Mesenchymal Stem Cells are Ideal for the Cell-based Treatment of Refractory Wounds: Strong Potential for Angiogenesis.

Although Mesenchymal Stem Cells (MSCs)-based therapy has been proposed as a promising strategy for the treatment of chronic lower-extremity ulcers, their optimal sources, amounts, and delivery methods are urgently needed to be determined. In this study, we compared the heterogeneity of the human MSCs derived from bone marrow (BMSCs), umbilical cord (UCMSCs), and adipose tissue (ADSCs) in accelerating wound healing and promoting angiogenesis and explored the underlying mechanism. Briefly, a diabetic rat model with a full-thickness cutaneous wound on the dorsal foot was developed. The wound was topically administered with three types of MSCs. Additionally, we carried out in vitro and in vivo analysis of the angiogenic properties of the MSCs. Moreover, the molecular mechanism of the heterogeneity of the MSCs derived from the three tissues was explored by transcriptome sequencing. When compared with the BMSCs- and UCMSCs-treated groups, the ADSCs-treated group exhibited markedly accelerated healing efficiency, characterized by increased wound closure rates, enhanced angiogenesis, and collagen deposition at the wound site. The three types of MSCs formed three-dimensional capillary-like structures and promoted angiogenesis in vitro and in vivo, with ADSCs exhibiting the highest capacity for tube formation and pro-angiogenesis. Furthermore, transcriptome sequencing revealed that ADSCs had higher expression levels of angiogenesis-associated genes. Our findings indicate that MSCs-based therapy accelerates the healing of ischemia- and diabetes-induced lower-extremity ulcers and that adipose tissue-derived MSCs might be ideal for therapeutic angiogenesis and treatment of chronic ischemic wounds.

Tumor growth inhibition-overall survival modeling in non-small cell lung cancer: A case study from GEMSTONE-302.

Overall survival is vital for approving new anticancer drugs but is often impractical for early-phase studies. The tumor growth inhibition-overall survival (TGI-OS) model could bridge the gap between early- and late-stage development. This study aimed to identify an appropriate TGI-OS model for patients with non-small cell lung cancer from the GEMSTONE-302 study of sugemalimab. We used three TGI models to delineate tumor trajectories and investigated three OS model for linking TGI metric to OS. All three TGI models accurately captured tumor profiles at the individual level. The published atezolizumab-based TGI-OS model predicted survival time satisfactorily through simulation-based evaluation, whereas the other published model built from multi-treatment underestimated OS. Our study-specific TGI-OS model identified time-to-growth as the most significant metric with the number of metastatic sites and neutrophil-to-lymphocyte ratio at baseline as covariates and exhibited robust OS predictability. Our findings demonstrated the effectiveness of the TGI-OS models in predicting phase III outcomes, which underpins their value as a powerful tool for antitumor drug development.