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Abstract Purpose To evaluate the therapeutic efficacy of intravenous amoxicillin clavulanate potassium combined with nebulized budesonide and ambroxol hydrochloride in pediatric community-acquired pneumonia (CAP) and its impact across various microbial strains and clinical symptoms. The primary objective of this study is to evaluate the efficacy of intravenous amoxicillin-clavulanate combined with nebulized budesonide and ambroxol hydrochloride in the treatment of pediatric community-acquired pneumonia (CAP), and to analyze their impact on different microbial strains and clinical symptoms. Secondary objectives include assessing the treatment's effect on the improvement of clinical symptoms, hospital stay duration, and the levels of inflammatory markers. Design Prospective, single-center study. Methods Fifty-six children with CAP, aged under 6 years, from Affiliated Maternity and Child Health Care Hospital of Nantong University were included. Patients were treated with conventional therapy and the study medication. Clinical characteristics, microbiological data, symptom improvement, and hospitalization times were analyzed. Findings Young children, particularly under 1 year, exhibited a higher incidence of multiple microbial infections and severe clinical manifestations. Treatment with budesonide and ambroxol hydrochloride led to significant clinical improvement across all age groups, with notable efficacy against various pathogens. Conclusions Nebulized budesonide and ambroxol hydrochloride are effective in treating pediatric CAP, offering a promising therapeutic option, particularly for young children with severe presentations.

Abstract The OVATE gene family plays an important role in regulating the development of plant organs and resisting stress, but its expression characteristics and functions in sorghum have not been revealed. In this study, we identified 26 OVATE genes in the sorghum BTx623 genome, which were divided into four groups and distributed unevenly across 9 chromosomes. Evolutionary analysis showed that after differentiation between sorghum and Arabidopsis, the OVATE gene family may have experienced unique expansion events, and all OVATE family members were negatively selected. Transcriptome sequencing and RT-qPCR results showed that OVATE genes in sorghum showed diverse expression characteristics, such as gene SORBl_3001G468900 and SORBl_3009G173400 were significantly expressed in seeds, while SORBI_3005G042700 and SORBI_3002G417700 were only highly expressed in L1. Meantime, in the promoter region, a large number of hormone-associated cis-acting elements were identified, and these results suggest that members of the OVATE gene family may be involved in regulating specific development of sorghum leaves and seeds. This study improves the understanding of the OVATE gene family of sorghum and provides important clues for further exploration of the function of the OVATE gene family.

Objective: To investigate the applicability of artificial intelligence-assisted diagnosis system in detecting pulmonary nodules and distinguishing benign and malignant nodules. Methods: Patients who underwent chest computed tomography (CT) from March 2022 to March 2023 at our hospital and who were followed-up with CT-guided needle biopsy or surgical procedures to determine the pathological nature were included in the study. The criteria for identifying true positive nodules were identified on the basis of the image analysis based on AI and two radiologists who identified suspicious lesions and referred to multiplanar reconstruction and three-dimensional reconstruction and other images to determine the existence of lung nodules; the findings from the two reports were consistent. The detection value of benign and malignant nodules obtained from AI and radiologists for true-positive nodules were compared. Results: AI detected 1337 nodules in 113 patients; radiologists detected 774 nodules, and verified the coexistence of 1079 true-positive nodules. The detection rate of true positive nodules (98.98%) by AI software was higher than that of radiologists (71.27%), the missed diagnosis rate (1.02%) was lower than that of radiologists (28.27%), and the misdiagnosis rate (23.91%) was higher than that of radiologists (0.46%). The true positive detection rate of AI for nodules with diameters 10 mm (98.08%) was slightly higher than that of radiologists (94.87%), but the difference was not statistically significant. Further large-sample clinical studies are needed to verify our findings. The detection rates of mixed ground-glass and calcified nodules (98.47%; 98.79%; 100.00%; 100.00%) from AI imaging were higher than those of the radiologists (75.52%; 68.02%; 72.73%; 84.66%). In the identification of benign and malignant nodules, 115 nodules in 113 patients were confirmed by pathological examination, of which 98 nodules were obtained by interventional surgery or CT-guided biopsy in our hospital, and 17 nodules were determined by follow-up diagnosis and during treatment at other hospitals. The sensitivity (97.47%), specificity (80.56%), and accuracy (92.17%) of the radiologists for the identification of benign and malignant nodules were higher than those of AI (93.67%, 66.67%, and 85.22%, respectively); however, the difference in sensitivity and specificity was not significant and might have been caused by sample selection bias. AI achieved high agreement with pathological results (Kappa value, 0.637), and radiologists achieved almost complete agreement (Kappa value, 0.811). Conclusion: AI-assisted diagnosis has a high detection rate and sensitivity for pulmonary nodules, which can greatly reduce the missed diagnosis rate, but increases the misdiagnosis rate. It can serve as an auxiliary aid for clinical diagnosis in identifying benign and malignant pulmonary nodules, but it cannot replace radiologists.

BackgroundMelastoma dodecandrum Lour. (MD), a traditional botanical drug known for its hypoglycemic, antioxidant, and anti-inflammatory properties, is commonly used to treat diabetes, osteoarthritis, and osteoporosis. However, its specific active components against diabetic osteoporosis remain unclear.PurposeThis study aimed to identify the key active components in MD using cell membrane chromatography coupled with mass spectrometry and validate their effects in vitro.MethodsAn AGEs-induced osteoblast injury model was established. MTT assays measured cell viability, and ALP activity was assessed using a biochemical kit. Western blotting was employed to detect the expression levels of osteoblast-related proteins OCN and RUNX2 and the AGE receptor protein RAGE. ELISA was used to determine the levels of SOD, MDA, CAT, and GPx. PCR quantified TNF-α expression to evaluate the protective effects and potential mechanisms of MD. The AGEs-induced osteoblast cell membrane chromatography-mass spectrometry method facilitated the rapid identification of potentially active compounds based on their affinity for the osteoblast cell membrane. Cell experiments further validated the activity of the characteristic component isovitexin.ResultsMD significantly improved cell viability in AGEs-damaged osteoblasts, enhanced ALP, SOD, CAT, and GPx activities, reduced MDA levels, increased OCN and RUNX2 protein expression, and decreased TNF-α mRNA and RAGE protein expression. Cell membrane chromatography identified 20 chemical constituents, including 13 flavonoids, 4 organic acids, 1 phenylpropanoids, 1 terpenoids, and 1 alkaloid. Cell experiments have confirmed that isovitexin has significant protective activity against osteoblasts and can inhibit the expression of specific receptor RAGE on the osteoblast membrane, consistent with the effect of MD.ConclusionMD and its active component, isovitexin, provide protective effects against AGEs-induced osteoblast injury, offering a basis for subsequent drug development.

Current knowledge graph-based recommendation methods heavily rely on high-quality knowledge graphs, often falling short in effectively addressing issues such as the cold start problem and heterogeneous noise in user interactions. This leads to biases in user interest and popularity. To overcome these challenges, this paper introduces a novel recommendation approach termed Knowledge-enhanced Perceptive Graph Attention with Graph Contrastive Learning (KPA-GCL), which leverages relational graph convolutional neural networks. The proposed method optimizes the triplet embedding representation of entity-item interactions based on relationships between adjacent entities in a heterogeneous graph. Subsequently, a graph convolutional neural network is employed for enhanced aggregation. Similarity scores from a contrastive view serve as the selection criterion for high-quality embedded representations, facilitating the extraction of refined knowledge subgraphs. Multiple adaptive contrast-loss optimization functions are introduced by combining Bayesian Personalized Ranking (BPR) and hard negative sampling techniques. Comparative experiments are conducted with ten popular existing methods using real public datasets. Results indicate that the KPA-GCL method outperforms compared methods in all datasets based on Recall, NDCG, Precision, and Hit-ratio measures. Furthermore, in terms of mitigating cold start and noise, the KPA-GCL method surpasses other ten methods. This validates the reasonability and effectiveness of KPA-GCL in real-world datasets.

Abstract Objective To create a deep‐learning automatic segmentation model for esophageal cancer (EC), metastatic lymph nodes (MLNs) and their adjacent structures using the UperNet Swin network and computed tomography angiography (CTA) images and to improve the effectiveness and precision of EC automatic segmentation and TN stage diagnosis. Methods Attention U‐Net, UperNet Swin, UNet++ and UNet were used to train the EC segmentation model to automatically segment the EC, esophagus, pericardium, aorta and MLN from CTA images of 182 patients with postoperative pathologically proven EC. The Dice similarity coefficient (DSC), sensitivity, and positive predictive value (PPV) were used to assess their segmentation effectiveness. The volume of EC was calculated using the segmentation results, and the outcomes and times of automatic and human segmentation were compared. All statistical analyses were completed using SPSS 25.0 software. Results Among the four EC autosegmentation models, the UperNet Swin had the best autosegmentation results with a DSC of 0.7820 and the highest values of EC sensitivity and PPV. The esophagus, pericardium, aorta and MLN had DSCs of 0.7298, 0.9664, 0.9496 and 0.5091. The DSCs of the UperNet Swin were 0.6164, 0.7842, 0.8190, and 0.7259 for T1‐4 EC. The volume of EC and its adjacent structures between the ground truth and UperNet Swin model were not significantly different. Conclusions The UperNet Swin showed excellent efficiency in autosegmentation and volume measurement of EC, MLN and its adjacent structures in different T stage, which can help to T and N stage diagnose EC and will save clinicians time and energy.

As an effective treatment for diabetes, islet transplantation has garnered significant attention and research in recent years. However, immune rejection and the toxicity of immunosuppressive drugs remain critical factors influencing the success of islet transplantation. While immunosuppressants are essential in reducing immune rejection reactions and can significantly improve the survival rate of islet transplants, improper use of these drugs can markedly increase mortality rates following transplantation. Additionally, the current availability of islet organ donations fails to meet the demand for organ transplants, making xenotransplantation a crucial method for addressing organ shortages. This review will cover the following three aspects: 1) the immune responses occurring during allogeneic islet transplantation, including three stages: inflammation and IBMIR, allogeneic immune response, and autoimmune recurrence; 2) commonly used immunosuppressants in allogeneic islet transplantation, including calcineurin inhibitors (Cyclosporine A, Tacrolimus), mycophenolate mofetil, glucocorticoids, and Bortezomib; and 3) early and late immune responses in xenogeneic islet transplantation and the immune effects of triple therapy (ECDI-fixed donor spleen cells (ECDI-SP) + anti-CD20 + Sirolimus) on xenotransplantation.

Background: To investigate the diagnostic value of computed tomography (CT)-guided aspiration biopsy combined with rapid field evaluation for pulmonary lesions. Methods: The PubMed and EMBASE databases were searched systematically for studies related to the diagnosis of lung lesions by CT-guided puncture biopsy combined with a rapid on-site indexed through October 2022. The updated Quality Assessment of Diagnostic Accuracy Studies (QUADAS-2) tool was applied as the main method to assess the risk of bias and applicability of the studies. Meta-analysis software was used to perform heterogeneity tests on the data. Based on the heterogeneity results, the appropriate effect model was selected to calculate the overall sensitivity, specificity, and diagnostic odds ratio (DOR), and to plot the summary receiver operating characteristic (SROC) curve, forest plot, and funnel plot. The results of the analysis of six studies (n=951) using a random-effects model showed pooled sensitivity, specificity, and diagnostic odds ratio with 95% confidence intervals of 94%, 95%, and 159.05, respectively, with an SROC AUC of 0.98. Further analysis of the four studies that established control groups showed that the sampling adequacy and diagnostic accuracy in the ROSE group were 12% and 13% higher than those in the non-ROSE group. In conclusion, CT-guided puncture biopsy combined with rapid on-site evaluation is a practical and feasible method for diagnosing pulmonary lesions and can be used as an important clinical diagnostic method.

Perforation of the tympanic membrane (TM) is a common condition that often requires a scaffold as a support for surgery. However, because of the external environment of the auditory canal, the scaffold could become bacterially infected and prevent the TM from healing. As a result, the perfect scaffold should have both antibacterial and biomimetic qualities. In this study, the biodegradable biomaterial poly(1,4-butylene carbonate) (PBC) films containing levofloxacin (LEV) was successfully prepared for the first time. The results showed that the hydrophilicity of the LEV/PBC film was improved after the addition of LEV, and the tensile strength was also complied with the requirements of the standard. The created antibacterial film demonstrated excellent antibacterial properties. In vitro hemolysis experiments revealed no risk of hemolysis for the new material, and the cytotoxicity study further confirmed its non-cytotoxic nature. Overall, LEV was a good component of PBC/LEV film, which is expected to be used for TM repair in the future.

In recent years, significant advancements in nanotechnology have yielded remarkable improvements in biomedical applications. Nanocarriers, harnessed from the principles of nanotechnology, have garnered widespread utilization in medicine delivery and diagnostics. However, the progression of nanocarriers has been hindered by two key challenges: low drug loading capacity and the potential for carrier-induced toxicity. To surmount these obstacles, the rapid development and expansion of carrier-free drug delivery systems (CFDDSs) composed of pure drugs and prodrugs have emerged as a promising solution. Extensive endeavors have been undertaken to explore novel excipients, therapeutic agents, self-assembly processes, and therapeutic mechanisms, aimed at expanding the horizons of CFDDSs and enhancing their therapeutic efficacy. This comprehensive review provides an overview of CFDDSs, elucidating their self-assembly mechanisms. Additionally, we examine their diverse biomedical applications while shedding light on the challenges ahead for the future development and clinical implementation of CFDDSs. This review serves to enhance our understanding of the intricate mechanisms governing drug nanoassembly formation and fosters the advancement of CFDDSs in the expansive realm of biomedical research.

AbstractContext Gualou Guizhi decoction (GLGZD) is an ancient Chinese classical prescription widely used to treat ischemic stroke. However, the molecular mechanisms of GLGZD promoting angiogenesis are unavailable.Objective This study investigates the angiogenesis effect of GLGZD as well as its mechanism.Materials and methods Ischemic stroke was established by middle cerebral artery occlusion/reperfusion (MCAO/R) in male Sprague-Dawley (SD) rats. The GLGZD groups received GLGZD (3.6, 7.2 and 14.4 g/kg) orally. Oxygen-glucose deprivation/reoxygenation (OGD/R) model was constructed in HUVECs receiving GLGZD medicated serum (MS). MRI, H&E staining, qRT-PCR, western blot and immunofluorescence methods were employed. miRNA210 inhibitor was employed to confirm the effects of GLGZD on promoting angiogenesis. Dual luciferase assay was used to verify the binding of miRNA210 with HIF mRNA.Results GLGZD treatment improved neurological function (by 27%), alleviated neuronal injury (by 76%), reduced infarct volume (by 74%) and increased microvessel density (by fourfold) in vivo. In vitro data had also shown that GLGZD caused proliferation of the cells (by 58%), their migration, and eventual formation of tubes (by threefold). Simultaneously, GLGZD enhanced the levels of angiogenesis-related molecules and activated the HIF/VEGF signalling pathway. Surprisingly, the beneficial effects of GLGZD on post-stroke angiogenesis and neurological recovery were weakened by miRNA210 inhibitor, and also abolished the mediation of proangiogenic factors. miRNA210 directly targeted HIF mRNA.Discussion and conclusions GLGZD enhances angiogenesis via activation of the miRNA210/HIF/VEGF signalling pathway, suggesting it can be a novel application as an effective angiogenic formula for stroke recovery.

PURPOSETo determine whether the morphological parameters of prostate zones and tumors on magnetic resonance imaging (MRI) can predict the tumor-stage (T-stage) of prostate cancer (PCa) and establish an optimal T-stage diagnosis protocol based on three-dimensional reconstruction and quantization after image segmentation.METHODSA dataset of the prostate MRI scans and clinical data of 175 patients who underwent biopsy and had pathologically proven PCa from January 2018 to November 2020 was retrospectively analyzed. The authors manually segmented and measured the volume, major axis, and cross-sectional area of the peripheral zone (PZ), transition zone, central zone (CZ), anterior fibromuscular stroma, and tumor. The differences were evaluated by the One-Way analysis of variance, Pearson’s chi-squared test, or independent samples t-test. Spearman’s correlation coefficient and receiver operating characteristic curve analyses were also performed. The cut-off values of the T-stage diagnosis were generated using Youden’s J index.RESULTSThe prostate volume (PV), PZ volume (PZV), CZ volume, tumor’s major axis (TA), tumor volume (TV), and volume ratio of the TV and PV were significantly different among stages T1 to T4. The cut-off values of the PV, PZV, CZV, TA, TV, and the ratio of TV/PV for the discrimination of the T1 and T2 stages were 53.63 cm3, 11.60 cm3, 1.97 cm3, 2.30 mm, 0.90 cm3, and 0.03 [area under the curves (AUCs): 0.628, 0.658, 0.610, 0.689, 0.724, and 0.764], respectively. The cut-off values of the TA, TV, and the ratio of TV/PV for the discrimination of the T2 and T3 stages were 2.80 mm, 8.29 cm3, and 0.12 (AUCs: 0.769, 0.702, and 0.688), respectively. The cut-off values of the TA, TV, and the ratio of TV/PV for the discrimination of the T3 and T4 stages were 4.17 mm, 18.71 cm3, and 0.22 (AUCs: 0.674, 0.709, and 0.729), respectively.CONCLUSIONThe morphological parameters of the prostate zones and tumors on the MRIs are simple and valuable diagnostic factors for predicting the T-stage of patients with PCa, which can help make accurate diagnoses and lateral treatment decisions.

Cognitive impairment is a core feature of schizophrenia, playing a pivotal role in the pathogenesis and prognosis of this disorder. Cognitive impairment in schizophrenia encompasses a wide range of domains, including processing speed, episodic memory, working memory, and executive function. These deficits persist throughout the course of the illness and significantly impact functional outcomes and quality of life. Therefore, it is imperative to identify the biological basis of cognitive deficits in schizophrenia and develop effective treatments. The role of N-methyl-D-aspartate (NMDA) receptors in synaptic transmission and plasticity has long been recognized, making them potential targets for schizophrenia treatment. This review will focus on emerging pharmacology targeting NMDA receptors, offering strategies for the prevention and treatment of cognitive deficits in schizophrenia.

Shaker potassium channel proteins are a class of voltage-gated ion channels responsible for K+ uptake and translocation, playing a crucial role in plant growth and salt tolerance. In this study, bioinformatic analysis was performed to identify the members within the Shaker gene family. Moreover, the expression patterns of rice Shaker(OsShaker) K+ channel genes were analyzed in different tissues and salt treatment by RT–qPCR. The results revealed that there were eight OsShaker K+ channel genes distributed on chromosomes 1, 2, 5, 6 and 7 in rice, and their promoters contained a variety of cis-regulatory elements, including hormone-responsive, light-responsive, and stress-responsive elements, etc. Most of the OsShaker K+ channel genes were expressed in all tissues of rice, but at different levels in different tissues. In addition, the expression of OsShaker K+ channel genes differed in the timing, organization and intensity of response to salt and chilling stress. In conclusion, our findings provide a reference for the understanding of OsShaker K+ channel genes, as well as their potential functions in response to salt and chilling stress in rice.

BackgroundThis retrospective observational cohort study aimed to evaluate whether tenecteplase’s use for acute ischemic stroke (AIS) has time management advantages and clinical benefits.Methods144 AIS patients treated with alteplase and 120 with tenecteplase were included. We compared baseline clinical characteristics, key reperfusion therapy time indices [onset-to-treatment time (OTT), door-to-needle time (DNT), and door-to-puncture time (DPT)] and clinical outcomes (24-h post-thrombolysis NIHSS improvement, and intracranial hemorrhage incidence) between the groups using univariate analysis. We assessed hospital stay durations and used binary logistic regression to examine tenecteplase’s association with DNT and DPT target times, NIHSS improvement, and intracranial hemorrhage.ResultsBaseline characteristics showed no significant differences except hyperlipidemia and atrial fibrillation. OTT (133 vs. 163.72, p = 0.001), DNT (36.5 vs. 50, p

Community detection in complex networks often suffers from insufficient data and limited utilization of prior knowledge. In this paper we propose “Semi-supervised Generative Adversarial Network” (GANSE), a novel algorithm that integrates Generative Adversarial Networks (GANs) and semi-supervised learning to address these challenges. This method addresses the issues above through a multi-step process. Initially, the network is rewired using vertex similarity metrics, thereby enhancing its structural integrity. Subsequently, a novel generative adversarial network model is designed, and our model facilitates the reconstruction of the network, thereby yielding partitions. Which form the basis for identifying core communities. Additionally, the local clustering coefficient is incorporated as a reward signal and injected into the node selection process. Moreover, isolated nodes are reallocated, ultimately culminating in the derivation of the final community structure. Experimental results on four large real-life datasets demonstrate the clear superiority of the proposed algorithm in terms of F1 and Jaccard metrics when compared to existing algorithms. Notably, our GANSE method outperforms the traditional algorithms in networks with “missing data”. Thus showing its robustness and effectiveness in real-world incomplete datasets. Our findings highlight the potential of GANs and semi-supervised learning for enhancing community detection accuracy in complex networks.

Salt and drought stress has been an important factor limiting agricultural production, and SA is an important phenolic involved in stress response, but the function of SA in response to dual salt and drought stress in rice is not clear. In this study, the effects and mechanisms of exogenous SA-triggered in rice adaptation to dual salt and drought stress were investigated by detecting physiological and biochemical indexes and the expression of salt and drought tolerance genes. The results showed that the application of SA could significantly increase the antioxidant enzyme activities of rice seedlings under salt and drought stress, thereby reducing the contents of rice H2O2 and MDA and maintaining the growth of rice seedlings. Moreover, the expression of genes involved in the response of abiotic stress, such as OsDREB2A, OsSAPK8, OsSAPK10 and OsMYB2, were up-regulated under salt and drought treatment, and SA application could further enhance the expression of those genes like OsDREB2A and OsSAPK8, suggesting that SA might regulate antioxidant enzyme activity via inducing the expression of salt and drought tolerance genes and enhancing the salt and drought tolerance of rice. The results will enrich the knowledge of the function of SA and provide a reference for studying the mechanism of SA in the salt and drought resistance of rice, and breeding new rice germplasm with improved salt and drought resistance.

The root microbiota plays a crucial role in assisting the plant host in combating various biotic and abiotic stresses, notably drought, which poses a significant threat to global food security. Despite extensive efforts to understand the shifts in rhizosphere and endosphere bacteriomes, there remains a gap in comprehending how drought stress influences the co-occurring network patterns within these compartments and their ecological functional potentials. To address this gap, a pot experiment was conducted with two treatments: continuous flooding as a control and drought treatment. Bulk soil, rhizosphere, and endosphere samples were collected and subjected to high-throughput sequencing and bioinformatics analysis. The results revealed that drought stress significantly reduced the rice biomass but increased the Shannon diversity index in both the rhizosphere and endosphere bacterial communities with no observable effect on richness across compartments. Additionally, drought treatment markedly altered the community structure and bacterial assemblages in these compartments, resulting in the specific enrichment of Actinobacteriota, Gemmatimonadetes, and Patescibacteria, while Bacteroidetes and Firmicutes were depleted in the rhizosphere and endosphere. Furthermore, drought heightened the complexity of the co-occurring networks and the proportions of positive links across all sampling compartments; this effect was accompanied by an increase in the number of connectors in the bulk soil and rhizosphere, as well as module hubs in the rhizosphere. Functional potential prediction indicated that drought stress significantly altered multiple potential ecological functions across all sampling compartments, particularly enriching functions related to the oxidation of sulfur, manganese, and hydrogen in the bulk soil, while functions associated with iron oxidation were significantly depleted in the rhizosphere. Overall, our results demonstrate that under drought stress, rice may specifically enrich certain bacterial taxa and enhance their positive interactions within its root system to improve adaptation.

Glioblastoma is the most common and malignant primary brain tumor, with high morbidity and mortality. Despite an aggressive, multimodal treatment regimen, including surgical resection followed by chemotherapy and radiotherapy, the prognosis of glioblastoma patients remains poor. One formidable challenge to advancing glioblastoma therapy is the complexity of the tumor microenvironment. The tumor microenvironment of glioblastoma is a highly dynamic and heterogeneous system that consists of not only cancerous cells but also various resident or infiltrating inflammatory cells. These inflammatory cells not only provide a unique tumor environment for glioblastoma cells to develop and grow but also play important roles in regulating tumor aggressiveness and treatment resistance. Targeting the tumor microenvironment, especially neuroinflammation, has increasingly been recognized as a novel therapeutic approach in glioblastoma. In this review, we discuss the components of the tumor microenvironment in glioblastoma, focusing on neuroinflammation. We discuss the interactions between different tumor microenvironment components as well as their functions in regulating glioblastoma pathogenesis and progression. We will also discuss the anti-tumor microenvironment interventions that can be employed as potential therapeutic targets.

This paper attempts to initiate the study of covers of finitely generated S-acts over monoids. We provide necessary and sufficient conditions for a monoid to ensure that n-generated S-acts have strongly flat covers, Condition (P) covers, and projective covers. The main conclusions extend some known results. We also show that Condition (P) covers of finitely generated S-acts are not unique, unlike strongly flat covers. Additionally, we demonstrate the property of Enochs’ X-precover of S-act A, where X denotes a class of S-acts that are closed under isomorphisms.