Plasma Concentrations of Contezolid and Its Efficacy and Safety in Elderly Patients with Multidrug-Resistant Tuberculosis and Renal Insufficiency.

As a new generation of oxazolidinone antibacterial drugs, contezolid has been shown to have comparable or even stronger activity than linezolid and has a low risk of adverse reactions such as bone marrow suppression toxicity. However, there are currently very few clinical reports and pharmacokinetic data of contezolid on the anti-tuberculosis therapy. Therefore, we report a case study of the pharmacokinetic study of contezolid in elderly patients with renal insufficiency and tuberculosis. The patient's condition improved after receiving an anti-tuberculosis regimen containing contezolid, with significant absorption of pleural effusion and lung plaques and nodules reduced. During the treatment, the patients' platelet and white blood cell levels fluctuated within normal ranges, but hemoglobin levels significantly decreased and did not recover after discontinuation of contezolid. The trough concentration of contezolid and the concentration at 2, 4, 6, and 10 h after administration were 1.27µg/mL, 3.88µg/mL, 6.32µg/mL, 8.99µg/mL, and 3.14µg/mL, respectively. The plasma concentrations of bedaquiline and cycloserine during the treatment were also monitored. This study demonstrated the efficacy and safety of contezolid in the treatment of multidrug-resistant tuberculosis and analyzed its pharmacokinetic changes in elderly patients with renal insufficiency, providing a reference for the clinical use of contezolid.

Therapeutic Drug Monitoring of Linezolid in Drug-Resistant Tuberculosis Patients: Clinical Factors and Hematological Toxicities.

Purpose: Previous studies have indicated that the development of severe adverse events is associated with linezolid peak concentration (Cmax), but the factors affecting linezolid Cmax and evidences on therapeutic drug monitoring to anticipate toxicity in drug-resistant tuberculosis (DR-TB) patients have not been clarified clearly. This study aimed to explore the factors influencing linezolid Cmax and investigate the association between linezolid concentration and hematological toxicity. Patients and Methods: This study included patients with drug-resistant tuberculosis treated with linezolid from January 2022 to September 2023. We analyzed the factors affecting linezolid Cmax using chi-squared and binary logistic regression. The diagnostic utility of linezolid Cmax in predicting hematological toxicity was evaluated using receiver operating characteristic (ROC) analysis. Results: A total of 76 patients were enrolled in the study. 63.20% met the standard rates for linezolid Cmax. Age (P=0.036), weight (P=0.0016), and creatinine clearance (P=0.0223) significantly correlated with the Cmax. Hematological toxicity was observed in 46.05% (35/76) of patients, characterized by thrombocytopenia (31.58%, 24/76), anemia (6.58%, 5/76), and leukopenia (21.05%, 16/76). ROC curve analysis confirmed the predictive value of linezolid Cmax for thrombocytopenia with an area under curve of 0.728. Conclusion: Suboptimal linezolid Cmax was prevalent among patients with DR-TB, with age, weight, and renal function emerging as influential factors. Elevated linezolid Cmax increases the risk of thrombocytopenia. Meticulous monitoring of linezolid Cmax is imperative during anti-DR-TB therapy to tailor treatment and mitigate hematological toxicity.

Model-based precision dosing and remedial dosing recommendations for delayed or missed doses of isoniazid in Chinese patients with tuberculosis.

AIMS: Isoniazid (INH) has been used as a first-line drug to treat tuberculosis (TB) for more than 50 years. However, large interindividual variability was found in its pharmacokinetics, and effects of nonadherence to INH treatment and corresponding remedy regime remain unclear. This study aimed to develop a population pharmacokinetic (PPK) model of INH in Chinese patients with TB to provide model-informed precision dosing and explore appropriate remedial dosing regimens for nonadherent patients. METHODS: In total, 1012 INH observations from 736 TB patients were included. A nonlinear mixed-effects modelling was used to analyse the PPK of INH. Using Monte Carlo simulations to determine optimal dosage regimens and design remedial dosing regimens. RESULTS: A 2-compartmental model, including first-order absorption and elimination with allometric scaling, was found to best describe the PK characteristics of INH. A mixture model was used to characterize dual rates of INH elimination. Estimates of apparent clearance in fast and slow eliminators were 28.0 and 11.2 L/h, respectively. The proportion of fast eliminators in the population was estimated to be 40.5%. Monte Carlo simulations determined optimal dosage regimens for slow and fast eliminators with different body weight. For remedial dosing regimens, the missed dose should be taken as soon as possible when the delay does not exceed 12 h, and an additional dose is not needed. delay for an INH dose exceeds 12 h, the patient only needs to take the next single dose normally. CONCLUSION: PPK modelling and simulation provide valid evidence on the precision dosing and remedial dosing regimen of INH.

Machine-learning-based classification of diffuse large B-cell lymphoma patients by a 7-mRNA signature enriched with immune infiltration and cell cycle / Clasificación basada en aprendizaje automático de pacientes con linfoma difuso de células B grandes mediante una firma de 7 ARNm enriquecida con infiltración inmune y ciclo celular

Background: Diffuse large B-cell lymphoma (DLBCL) exhibits remarkable heterogeneity but still remains undiagnosed in identifying the subpopulation of DLBCL to predict the prognosis and guide clinical treatment. Methods: Molecular subgroups were identified in gene expression data from GSE10846 by a consensus clustering algorithm. And gene set enrichment analysis, immune infiltration, and the proposed cell cycle algorithm were applied to explore the biological functions of different subtypes. Meanwhile, univariate and multivariate Cox regression analyses were used to evaluate independent prognostic factors of DLBCL. Finally, the prognostic model, including some key genes screened by Lasso regression, Random Forest algorithm, and point-biserial correlation, was constructed by an optimal classifier from seven machine learning algorithms and validated by another three external datasets (GSE34171, GSE87371, GSE31312). Results: Comprehensive genomic analysis of 1,143 DLBCL samples identify 2 molecularly, prognostically relevant subtypes: immune-enriched (IME) and cell-cycle-enriched (CCE). Then a new predictive model including seven key genes (SERPING1, TIMP2, NME1, DCTPP1, RFC4, POLE2, and SNRPD1) was developed with high prediction accuracy (88.6%) and strong predictive power (AUC = 0.973) based on the Support Vector Machine (SVM) algorithm in 414 patients from GSE10846. The predictive power was similar in another three testing sets (HR > 1.400, p < 0.05). Conclusion: This model could evaluate survival independently with strong predictive power compared with other clinical risk factors. Our study constructed a reliable model to predict two new subtypes of DLBCL patients, which could guide the implementation of individualized treatment.(AU)

Machine-learning-based classification of diffuse large B-cell lymphoma patients by a 7-mRNA signature enriched with immune infiltration and cell cycle.

BACKGROUND: Diffuse large B-cell lymphoma (DLBCL) exhibits remarkable heterogeneity but still remains undiagnosed in identifying the subpopulation of DLBCL to predict the prognosis and guide clinical treatment. METHODS: Molecular subgroups were identified in gene expression data from GSE10846 by a consensus clustering algorithm. And gene set enrichment analysis, immune infiltration, and the proposed cell cycle algorithm were applied to explore the biological functions of different subtypes. Meanwhile, univariate and multivariate Cox regression analyses were used to evaluate independent prognostic factors of DLBCL. Finally, the prognostic model, including some key genes screened by Lasso regression, Random Forest algorithm, and point-biserial correlation, was constructed by an optimal classifier from seven machine learning algorithms and validated by another three external datasets (GSE34171, GSE87371, GSE31312). RESULTS: Comprehensive genomic analysis of 1,143 DLBCL samples identify 2 molecularly, prognostically relevant subtypes: immune-enriched (IME) and cell-cycle-enriched (CCE). Then a new predictive model including seven key genes (SERPING1, TIMP2, NME1, DCTPP1, RFC4, POLE2, and SNRPD1) was developed with high prediction accuracy (88.6%) and strong predictive power (AUC = 0.973) based on the Support Vector Machine (SVM) algorithm in 414 patients from GSE10846. The predictive power was similar in another three testing sets (HR > 1.400, p < 0.05). CONCLUSION: This model could evaluate survival independently with strong predictive power compared with other clinical risk factors. Our study constructed a reliable model to predict two new subtypes of DLBCL patients, which could guide the implementation of individualized treatment.

Preparation, Structural Characterization, and Enzymatic Properties of Alginate Lyase Immobilized on Magnetic Chitosan Microspheres.

Alginate lyase is an enzyme that catalyses the hydrolysis of alginate into alginate oligoalginates. To enhance enzyme stability and recovery, a facile strategy for alginate lyase immobilization was developed. Novel magnetic chitosan microspheres were synthesized and used as carriers to immobilize alginate lyase. The immobilization of alginate lyase on magnetic chitosan microspheres was successful, as proven by Fourier transform infrared spectroscopy and X-ray diffraction spectra. Enzyme immobilization exhibited the best performance at an MCM dosage of 1.5 g/L, adsorption time of 2.0 h, glutaraldehyde concentration of 0.2%, and immobilization time of 2.0 h. The optimal pH of the free alginate lyase was 7.5, and this pH value was shifted to 8.0 after immobilization. No difference was observed at the optimal temperature (45 °C) for the immobilized and free enzymes. The immobilized alginate lyase displayed better thermal stability than the free alginate lyase. The Km values of the free and immobilized enzymes were 0.05 mol/L and 0.09 mol/L, respectively. The immobilized alginate lyase retained 72% of its original activity after 10 batch reactions. This strategy was found to be a promising method for immobilizing alginate lyase.

A 4.7-kDa polysaccharide from Panax ginseng suppresses Aß pathology via mitophagy activation in cross-species Alzheimer's disease models.

Alzheimer's disease (AD) is a neurological condition that progresses with age. Amyloid-ß (Aß) aggregation has been suggested to be a key pathogenic process in Alzheimer's disease. Ginseng polysaccharides (GP), the main biologically active components isolated from Panax ginseng C. A. Meyer (ginseng), may act as neuroprotective agents with potential benefits for AD patients. However, GP effects on Aß pathology and AD symptoms are still unclear. Here, a 4.7-kDa GP termed GP4 was purified and subjected to basic physicochemical characterization. The biological effects of GP4 to prevent Aß aggregation were then assessed with cross-species AD models, including Aftin-5-treated SH-SY5Y cells and cerebral organoids, and transgenic C. elegans overexpressing the full-length human Aß42 peptide. These analyses ultimately demonstrated that GP4 was capable of inhibiting Aß accumulation both in vivo and vitro, and with early intervention of GP4 being sufficient to alleviate Aß42-associated aging phenotypes and memory loss in C. elegans model of AD. Furthermore, neuroinflammation was significantly down-regulated in human cells and cerebral organoids. From a mechanistic perspective, the ability of GP4 to inhibit Aß aggregation was found to be related to its ability to promote neuronal mitophagic activity. This finding offers a robust theoretical foundation for the further development of GP4 as a candidate drugs with the potential to treat AD.

Constructing Hollow Multishelled Microreactors with a Nanoconfined Microenvironment for Ofloxacin Degradation through Peroxymonosulfate Activation: Evolution of High-Valence Cobalt-Oxo Species.

This study constructed hollow multishelled microreactors with a nanoconfined microenvironment for degrading ofloxacin (OFX) through peroxymonosulfate (PMS) activation in Fenton-like advanced oxidation processes (AOPs), resulting in adequate contaminant mineralization. Among the microreactors, a triple-shelled Co-based hollow microsphere (TS-Co/HM) exhibited optimal performance; its OFX degradation rate was 0.598 min-1, which was higher than that of Co3O4 nanoparticles by 8.97-fold. The structural tuning of Co/HM promoted the formation of oxygen vacancies (VO), which then facilitated the evolution of high-valence cobalt-oxo (Co(IV)═O) and shifted the entire t2g orbital of the Co atom upward, promoting catalytic reactions. Co(IV)═O was identified using a phenylmethyl sulfoxide (PMSO) probe and in situ Raman spectroscopy, and theoretical calculations were conducted to identify the lower energy barrier for Co(IV)═O formation on the defect-rich catalyst. Furthermore, the TS-Co/HM catalyst exhibited remarkable stability in inorganic (Cl-, H2PO4-, and NO3-), organic (humic acid), real water samples (tap water, river water, and hospital water), and in a continuous flow system in a microreactor. The nanoconfined microenvironment could enrich reactants in the catalyst cavities, prolong the residence time of molecules, and increase the utilization efficiency of Co(IV)═O. This work describes an activation process involving Co(IV)═O for organic contaminants elimination. Our results may encourage the use of multishelled structures and inform the design of nanoconfined catalysts in AOPs.

Dual-Role of Polyelectrolyte-Tethered Benzimidazolium Cation in Promoting CO2 /Pure Water Co-Electrolysis to Ethylene.

Electrochemical CO2 reduction reaction (CO2 RR), as a promising route to realize negative carbon emissions, is known to be strongly affected by electrolyte cations (i.e., cation effect). In contrast to the widely-studied alkali cations in liquid electrolytes, the effect of organic cations grafted on alkaline polyelectrolytes (APE) remains unexplored, although APE has already become an essential component of CO2 electrolyzers. Herein, by studying the organic cation effect on CO2 RR, we find that benzimidazolium cation (Beim+ ) significantly outperforms other commonly-used nitrogenous cations (R4 N+ ) in promoting C2+ (mainly C2 H4 ) production over copper electrode. Cyclic voltammetry and in situ spectroscopy studies reveal that the Beim+ can synergistically boost the CO2 to *CO conversion and reduce the proton supply at the electrocatalytic interface, thus facilitating the *CO dimerization toward C2+ formation. By utilizing the homemade APE ionomer, we further realize efficient C2 H4 production at an industrial-scale current density of 331 mA cm-2 from CO2 /pure water co-electrolysis, thanks to the dual-role of Beim+ in synergistic catalysis and ionic conduction. This study provides a new avenue to boost CO2 RR through the structural design of polyelectrolytes.

Integrative analysis identifies two molecular and clinical subsets in Luminal B breast cancer.

Comprehensive multiplatform analysis of Luminal B breast cancer (LBBC) specimens identifies two molecularly distinct, clinically relevant subtypes: Cluster A associated with cell cycle and metabolic signaling and Cluster B with predominant epithelial mesenchymal transition (EMT) and immune response pathways. Whole-exome sequencing identified significantly mutated genes including TP53, PIK3CA, ERBB2, and GATA3 with recurrent somatic mutations. Alterations in DNA methylation or transcriptomic regulation in genes (FN1, ESR1, CCND1, and YAP1) result in tumor microenvironment reprogramming. Integrated analysis revealed enriched biological pathways and unexplored druggable targets (cancer-testis antigens, metabolic enzymes, kinases, and transcription regulators). A systematic comparison between mRNA and protein displayed emerging expression patterns of key therapeutic targets (CD274, YAP1, AKT1, and CDH1). A potential ceRNA network was developed with a significantly different prognosis between the two subtypes. This integrated analysis reveals a complex molecular landscape of LBBC and provides the utility of targets and signaling pathways for precision medicine.

CHDH, a key mitochondrial enzyme, plays a diagnostic role in metabolic disorders diseases and tumor progression.

Human choline dehydrogenase (CHDH) is a transmembrane protein located in mitochondria. CHDH has been shown to be one of the important catalytic enzymes that catalyze the oxidation of choline to betaine and is involved in mitochondrial autophagy after mitochondrial damage. In recent years, an increasing number of studies have focused on CHDH and found a close association with the pathogenesis of various diseases, including tumor prognosis. Here we summarized the genomic localization, protein structure and basic functions of CHDH and discuss the progress of CHDH research in metabolic disorders and other diseases. Moreover, we described the regulatory role of CHDH on the progression of different types of malignant tumors. In addition, major pathogenic mechanisms of CHDH in multiple diseases may be associated with single nucleotide polymorphism (SNP). We look forward to providing new strategies and basis for clinical diagnosis and prognosis prediction of diseases by diagnosing SNP loci of CHDH genes. Our work evaluates the feasibility of CHDH as a molecular marker relevant to the diagnosis of some metabolic disorders diseases and tumors, which may provide new targets for the treatment of related diseases and tumors.

Individualized Pharmaceutical Care for Antifungal Therapy in a Patient with Aspergillus tubingensis Spondylitis After Discontinuation of Rifampicin: A Case Report.

Aspergillus tubingensis spondylitis (AS) is a rare spinal infectious disease with severe clinical symptoms and a challenging diagnosis. Treatment of AS is challenging due to its prolonged duration, substantial side effects, and complex drug-drug interactions. However, there is a lack of experience in individualized pharmaceutical care of AS by clinical pharmacists, especially in the presence of rifampicin, which has sustained liver enzyme induction after discontinuation. Our case described an immunocompetent patient infected with Aspergillus tubingensis spondylitis. Clinical pharmacists proposed an individualized treatment regimen for AS, after considering the effects of sustained liver enzyme induction of rifampicin (after discontinuation) on voriconazole, and utilized caspofungin as a bridge-connection scheme. We also paid attention to changes in indicators during treatment and managed adverse reactions. Therapeutic drug monitoring of voriconazole was also used to optimize the dosing regimen. With the individualized pharmaceutical care of clinical pharmacists and the efforts of clinicians, the patient's incision healed well after 33 days of hospitalization, and she was discharged with significant improvement. Therefore, individualized pharmaceutical care by a clinical pharmacist can help optimize the treatment of Aspergillus tubingensis spondylitis. In clinical practice, drug-drug and drug-diet interactions may affect voriconazole efficacy, and individualized dose adjustment using therapeutic drug monitoring (TDM) is critical to improve efficacy and reduce adverse reactions.

Parametric population pharmacokinetics of isoniazid: a systematic review.

INTRODUCTION: Isoniazid (INH) plays an important role in prevention and treatment of tuberculosis (TB). However, large pharmacokinetic (PK) variations are observed in patients receiving standard INH dosages. Considering the influence of PK variations on INH efficacy or adverse reactions, we reviewed the population PK studies of INH and explored significant covariates that influence INH PK. METHODS: The PubMed and Embase databases were systematically searched from their inception to 30 January 2023. PPK studies on INH using a parametric nonlinear mixed-effect approach were included in this review. The characteristics and identified significant covariates of the included studies were summarized. RESULTS: Twenty-one studies conducted in adults, and seven in pediatrics were included. A two-compartment model with first-order absorption and elimination was the frequently used structural model for INH. NAT2 genotype, body size, and age were identified as significant covariates affecting INH PK variation. The median clearance (CL) value in the fast metabolizers was 2.55-fold higher than that in the slow metabolizers. Infants and children had higher CL per weight values than adults with the same metabolic phenotype. In pediatric patients, CL value increased with postnatal age. CONCLUSIONS: Compared with slow metabolizers, the daily dose of INH should be increased by 200-600 mg in fast metabolizers. To achieve effective treatment, pediatric patients need a higher dose per kilogram than adults. Further PPK studies of anti-tuberculosis drugs are needed to comprehensively understand the covariates that affect their PK characteristics and to achieve accurate dose adjustments.

Research and Application of Energy-Efficient Management Approach for Wireless Sensor Networks.

Wireless sensor networks (WSNs) are widely used in industrial applications. However, many of them have limited lifetimes, which has been a considerable constraint on their widespread use. As a typical application of WSNs, distributed measurement of the electric field under high-voltage direct-current (HVDC) transmission lines also suffers from this issue. This paper first introduces the composition of the electric-field measurement system (EFMS) and its working principle. Considering the actual power supply of the system, this paper mainly introduces the composition of the wireless sensor node (WSND) and analyzes the power consumption and potential working state transformation of the WSND, together with a comprehensive study on parameters affecting the power consumption of the wireless communication unit. Moreover, an energy-efficient scheduling approach is proposed after specially designing a working sequence and the study on system parameters. The proposed approach is verified by experiments on not only the experimental line of the national HVDC test base, but also a commercial operation HVDC transmission line with the challenge of long endurance, which is considered in this paper with a new strategy. The results show that the proposed method can greatly extend the lifetime of the WSND.

Modulating tumour vascular normalisation using triptolide-loaded NGR-functionalized liposomes for enhanced cancer radiotherapy.

Radiotherapy is an effective therapy in tumour treatment. However, the characteristics of the tumour microenvironment, including hypoxia, low pH, and interstitial fluid pressure bring about radioresistance. To improve the anti-tumour effect of radiotherapy, it has been demonstrated that antiangiogenic therapy can be employed to repair the structural and functional defects of tumour angiogenic vessels, thereby preventing radioresistance or poor therapeutic drug delivery. In this study, we prepared triptolide (TP)-loaded Asn-Gly-Arg (NGR) peptide conjugated mPEG2000-DSPE-targeted liposomes (NGR-PEG-TP-LPs) to induce tumour blood vessel normalisation, to the end of increasing the sensitivity of tumour cells to radiotherapy. Further, to quantify the tumour vessel normalisation window, the structure and functionality of tumour blood vessels post NGR-PEG-TP-LPs treatment were evaluated. Thereafter, the anti-tumour effect of radiotherapy following these treatments was evaluated using HCT116 xenograft-bearing mouse models based on the tumour vessel normalisation period window. The results obtained showed that NGR-PEG-TP-LPs could modulate tumour vascular normalisation to increase the oxygen content of the tumour microenvironment and enhance the efficacy of radiotherapy. Further, liver and kidney toxicity tests indicated that NGR-PEG-TP-LPs are safe for application in cancer treatment.

Analysis of growth dynamics in five different media and metabolic phenotypic characteristics of Piriformospora indica.

Piriformospora indica is an important endophytic fungus with broad potential for alleviating biotic and abiotic stress on host plants. This study monitored the growth dynamics of P. indica on five commonly used artificial media for microorganisms and analyzed its metabolic characteristics using Biolog Phenotype Microarray (PM) technology. The results showed that P. indica grew fastest on Potato Dextrose Agar (PDA), followed by Kidney Bean Agar (KBA), Alkyl Ester Agar (AEA), Oatmeal Agar (OA), and Luria-Bertani Agar (LB), and the most suitable medium for spore production was OA. Using Biolog PM1-10, 950 metabolic phenotypes of P. indica were obtained. P. indica could metabolize 87.89% of the tested carbon sources, 87.63% of the tested nitrogen sources, 96.61% of the tested phosphorus sources, and 100% of the tested sulfur sources. P. indica displayed 92 kinds of tested biosynthetic pathways, and it could grow under 92 kinds of tested osmotic pressures and 88 kinds of tested pH conditions. PM plates 1-2 revealed 43 efficient carbon sources, including M-Hydroxyphenyl acid, N-Acetyl-D-Glucosamine, Tyramine, Maltotrios, α-D-Glucosine, I-Erythritol, L-Valine, D-Melezitose, D-Tagatose, and Turanose. PM plates 3,6-8 indicated 170 efficient nitrogen sources, including Adenosine, Inosine Allantoin, D, L-Lactamide, Arg-Met, lle-Trp, Ala-Arg, Thr-Arg, Trp-Tyr, Val-Asn, Gly-Gly-D-Leu, Gly-Gly-Phe, and Leu-Leu-Leu. This study demonstrates that P. indica can metabolize a variety of substrates, such as carbon and nitrogen sources, and has a wide range of environmental adaptability. The growth dynamics on artificial culture media and metabolic phenotypes of P. indica can be used to investigate its biological characteristics, screen for more suitable growth and sporulation conditions, and elucidate the physiological mechanisms that enhance the stress resistance of host plants. This study provides a theoretical basis for its better application in agriculture.

A 5-Pathway Signature Predicts Prognosis Based on Immune-Derived lncRNAs in Patients with Breast Cancer.

Background: Currently, predictive models were not developed based on the signaling pathway signatures of immune-related lncRNAs in breast cancer (BRCA) patients. Methods: We selected unsupervised hierarchical clustering algorithm to classify patients with BRCA based on the significant immune-derived lncRNAs from the TCGA dataset. And different methods including ESTIMATE, ImmuneCellAI, and CIBERSORT were performed to evaluate the immune infiltration of tumor microenvironment. Using Lasso regression algorithm, we filtered the significant signaling pathways enriched by GSEA, GSVA, or PPI analysis to develop a prognostic model. And a nomogram integrated with clinical factors and significant pathways was constructed to predict the precise probability of overall survival (OS) of BRCA patients in the TCGA dataset (n = 1,098) and another two testing sets (n = 415). Results: BRCA patients were stratified into the PC (n = 571) and GC (n = 527) subgroup with significantly different prognosis with 550 immune-related lncRNAs in the TCGA dataset. Integrated analysis revealed different immune response, oncogenic signaling, and metabolic reprograming pathways between these two subgroups. And a 5-pathway signature could predict the prognosis of BRCA patients between these two subgroups independently in the TCGA dataset, which was confirmed in another two cohorts from the GEO dataset. In the TCGA dataset, 5-year OS rate was 78% (95% CI: 73-84) vs. 82% (95% CI: 77-87) for the PC and GC group (HR = 1.63 (95% CI: 1.17-2.28), p = 0.004). The predictive power was similar in another two testing sets (HR > 1.20, p < 0.01). Finally, a nomogram is developed for clinical application, which integrated this signature and age to accurately predict the survival probability in BRCA patients. Conclusion: This 5-pathway signature correlated with immune-derived lncRNAs was able to precisely predict the prognosis for patients with BRCA and provided a rich source characterizing immune-related lncRNAs and further informed strategies to target BRCA vulnerabilities.

Latamoxef-induced severe thrombocytopenia during the treatment of pulmonary infection: A case report.

BACKGROUND: Latamoxef shows excellent antibacterial activity against anaerobic bacteria such as Bacteroides fragilis. Reports of thrombocytopenic toxicity of latamoxef are limited. This report presents a case of severe thrombocytopenia possibly induced by latamoxef, an infrequent adverse drug reaction in a young patient with tuberculosis and Crohn's disease in China. CASE SUMMARY: We reported a case of severe thrombocytopenia induced by latamoxef in a 28-year-old man with tuberculosis and Crohn's disease. On admission, the patient presented with a cough productive of bloody sputum, a chest computed tomogram suggested scattered mottled, high-density shadows in both lungs. Laboratory tests indicated a platelet count of 140000/µL. Considered a pulmonary bacterial infection, the patient received anti-infection therapy with latamoxef (dose: 2.0 g) intravenously Q12h. On the 9th day of treatment, the platelet count decreased to 44000/µL. On the 12th day, scattered purpura and ecchymosis appeared on the patient's limbs and trunk, and the platelet count decreased to 9000/µL after latamoxef treatment for 15 d. Three days after discontinuation of latamoxef, the platelet count recovered to 157000/µL, and the area of scattered purpura and ecchymosis on the limbs and trunk decreased. The platelet counts remained in the normal range, and no thrombocytopenia was found at follow-up 15 mo after discharge. CONCLUSION: For patients treated with latamoxef, platelet counts should be carefully followed, and caregivers should be vigilant for the appearance of scattered ecchymosis.

Mechanism underlying linezolid-induced peripheral neuropathy in multidrug-resistant tuberculosis.

Multidrug-resistant tuberculosis (MDR-TB) remains a main global health concern as there is no comprehensive therapeutic intervention yet and numerous adverse effects follow the therapeutic process. In recent years, linezolid has been frequently used for treating MDR-TB. However, peripheral neuropathy associated with linezolid has reduced patient compliance. The current study explored the mechanism underlying linezolid-induced peripheral neuropathy in MDR-TB. Autophagy plays a neuroprotective role against peripheral nerve injury. We hypothesized that autophagy might also play a neuroprotective role against linezolid-induced peripheral neuropathy. In this study, we collected 12 questionnaires from MDR-TB patients in our hospital, and 10 of them developed linezolid-induced pain. The pain is mainly concentrated in the feet and accompanied by numbness. Subsequently, we used Sprague-Dawley (SD) rats and Schwann cells (SCs) to explore the mechanism. We found that linezolid causes a sparse arrangement of sciatic nerve tissue with associated loss of neurons, myelin sheaths, and down-regulation of LC3B expression. These results were also confirmed by in vitro experiments, showing that linezolid inhibited the proliferation of SCs. And the expression of P-AKT and P62 was elevated, and the expression of LC3B declined compared with the control group. Moreover, chloroquine (CQ), an autophagy inhibitor, also exhibited experimental results similar to linezolid. In summary, we conclude that linezolid-induced peripheral neuropathy is associated with the inhibition of autophagy flux.