Thermal ablation versus liver resection for hepatocellular carcinoma in patients with cirrhosis: a systematic review and meta-analysis of propensity-score matched studies.

The outcomes of cirrhotic patients with hepatocellular carcinoma (HCC) after thermal ablation (TA) versus liver resection (LR) are debated. We aimed to compare the overall survival (OS), disease-free survival (DFS), and operative outcomes after TA and LR for HCC in patients with cirrhosis. Until November 15, 2022, we searched PubMed, Embase, and Cochrane databases by using Medical Subject Heading terms and other terms, and used the Newcastle-Ottawa literature evaluation scale to assess the quality of selected studies. OS, DFS, and operative outcomes were extracted and analyzed. The meta-analysis showed that 5 propensity-score matched (PSM) studies including 933 patients (463 TA vs. 470 LR) were included. After analysis, TA and LR had similar results at 1-year OS (odds ratio [OR] 1.68; 95% confidence interval [CI] 1.01-2.78; P = 0.05) and 3-year OS (OR 0.76; 95% CI 0.56-1.04; P = 0.08), whereas LR increased 5-years OS (OR 0.37; 95% CI 0.18-0.74; P = 0.005). In addition to the DFS, the 1-year DFS was significantly higher in patients with LR. However, there were no obvious differences in 3-year and 5-year DFS when comparing TA and LR. The length of operative time and hospital stay were longer in the LR group. Besides, the LR group had significantly higher rate of perioperative blood transfusions and major complications. Our research proved that LR took advantage of OS and DFS for HCC patients with cirrhosis. Additional well-designed randomized controlled trials are needed.

Deep Learning Methods in Medical Image-Based Hepatocellular Carcinoma Diagnosis: A Systematic Review and Meta-Analysis.

(1) Background: The aim of our research was to systematically review papers specifically focused on the hepatocellular carcinoma (HCC) diagnostic performance of DL methods based on medical images. (2) Materials: To identify related studies, a comprehensive search was conducted in prominent databases, including Embase, IEEE, PubMed, Web of Science, and the Cochrane Library. The search was limited to studies published before 3 July 2023. The inclusion criteria consisted of studies that either developed or utilized DL methods to diagnose HCC using medical images. To extract data, binary information on diagnostic accuracy was collected to determine the outcomes of interest, namely, the sensitivity, specificity, and area under the curve (AUC). (3) Results: Among the forty-eight initially identified eligible studies, thirty studies were included in the meta-analysis. The pooled sensitivity was 89% (95% CI: 87-91), the specificity was 90% (95% CI: 87-92), and the AUC was 0.95 (95% CI: 0.93-0.97). Analyses of subgroups based on medical image methods (contrast-enhanced and non-contrast-enhanced images), imaging modalities (ultrasound, magnetic resonance imaging, and computed tomography), and comparisons between DL methods and clinicians consistently showed the acceptable diagnostic performance of DL models. The publication bias and high heterogeneity observed between studies and subgroups can potentially result in an overestimation of the diagnostic accuracy of DL methods in medical imaging. (4) Conclusions: To improve future studies, it would be advantageous to establish more rigorous reporting standards that specifically address the challenges associated with DL research in this particular field.

Proteomic Study of the Adaptive Mechanism of Ciprofloxacin-Resistant Staphylococcus aureus to the Host Environment.

Antibiotic-resistant bacteria can escape host immune killing and settle in the host to form persistent infections. In this study we investigated the adaptive mechanism of resistant Staphylococcus aureus to the host environment by data-independent acquisition-based quantitative proteomics and functional validation. The growth curve and minimum inhibitory concentration (MIC) indicated that ciprofloxacin-resistant (Cip-R) S. aureus showed a survival advantage over sensitive strains. Cip-R also exhibited a stronger invasion and biofilm formation ability than sensitive bacteria. Cip-R stimulation resulted in the improved production of inflammatory factors of the host cells. Proteomics study combined with biochemical validations showed that Cip-R obtained adaptability to the host via upregulation of the tricarboxylic acid cycle (TCA cycle) and downregulation of ribosome metabolism and protein folding to maintain energy to support Cip-R's survival. Thus, this study will help us to further explain the growth strategy of resistant bacteria to adapt to the host environment, and provide important information for the development of new antibacterial drugs.

The predictive value of the HEART and GRACE scores for major adverse cardiac events in patients with acute chest pain.

The history, electrocardiogram, age, risk factors, troponin (HEART) and global registry of acute coronary events (GRACE) scoring systems are commonly used to risk stratify patients with chest pain. This study investigated the application of these scores in predicting the short-term risk of a major adverse cardiac event (MACE) in patients with chest. A total of 509 patients were analyzed. All patients were followed up for 30 days after visiting our emergency department. At 30 days post-admission, the primary outcome (MACE) was recorded in 92 patients (18.1%), 88 (95.6%) of whom had experienced an acute myocardial infarction. Thirty-seven (40.2%) of the patients with a MACE underwent percutaneous coronary intervention and six patients (6.5%) died. The HEART and GRACE scores were both significantly higher in patients who developed a MACE than in those without (P < 0.05). The HEART and GRACE scores had c-statistic values of 0.811 (95% CI 0.774-0.844) and 0.648 (95% CI 0.603-0.688), respectively. The Hosmer-Lemeshow statistic revealed that the HEART and GRACE scores had values of 8.68 (P = 0.39) and 10.45 (P = 0.11), respectively. The percentages of patients with HEART scores of 0-3, 4-6, and 7-10 were 3.0%, 26.2%, and 46.3%, respectively, in those with a MACE within 30 days. The findings show that while both scoring systems are useful, the HEART score is superior to the GRACE score for predicting the occurrence of MACE within 30 days in patients with chest pain.

Photocatalytic Protein Damage by Silver Nanoparticles Circumvents Bacterial Stress Response and Multidrug Resistance.

Silver nanoparticles (AgNPs) are known for their broad-spectrum antibacterial properties, especially against antibiotic-resistant bacteria. However, the bactericidal mechanism of AgNPs remains unclear. In this study, we found that the bactericidal ability of AgNPs is induced by light. In contrast to previous postulates, visible light is unable to trigger silver ion release from AgNPs or to promote AgNPs to induce reactive oxygen species (ROS) in Escherichia coli In fact, we revealed that light excited AgNPs to induce protein aggregation in a concentration-dependent manner in E. coli, indicating that the bactericidal ability of AgNPs relies on the light-catalyzed oxidation of cellular proteins via direct binding to proteins, which was verified by fluorescence spectra. AgNPs likely absorb the light energy and transfer it to the proteins, leading to the oxidation of proteins and thus promoting the death of the bacteria. Isobaric tags for relative and absolute quantitation (iTRAQ)-based proteomics revealed that the bacteria failed to develop effective resistance to the light-excited AgNPs. This direct physical mechanism is unlikely to be counteracted by any known drug resistance mechanisms of bacteria and therefore may serve as a last resort against drug resistance. This mechanism also provides a practical hint regarding the antimicrobial application of AgNPs-light exposure improves the efficacy of AgNPs.IMPORTANCE Although silver nanoparticles (AgNPs) are well known for their antibacterial properties, the mechanism by which they kill bacterial cells remains a topic of debate. In this study, we uncovered the bactericidal mechanism of AgNPs, which is induced by light. We tested the efficacy of AgNPs against a panel of antimicrobial-resistant pathogens as well as Escherichia coli under conditions of light and darkness and revealed that light excited the AgNPs to promote protein aggregation within the bacterial cells. Our report makes a significant contribution to the literature because this mechanism bypasses microbial drug resistance mechanisms, thus presenting a viable option for the treatment of multidrug-resistant bacteria.

The mechanism of iron-compensation for manganese deficiency of Streptococcus pneumoniae.

Given their involvement in catalysis, infection, and biofilm formation, Fe and Mn are essential for bacterial survival and virulence. In this study, we found that Streptococcus pneumoniae (S. pneumoniae) could grow in the Mn-deficient medium (MDCM). Furthermore, findings showed that the Fe concentration in the bacterium increased when the Mn concentration decreased. In addition, it was noted that supplementing MDCM with Fe resulted in the recovery of bacterial growth. Quantitative proteomics using stable-isotope dimethyl labeling was performed to investigate the adaptive growth mechanism of S. pneumoniae under Mn-deficient conditions. It was found that the expression levels of 25 proteins were downregulated, whereas those of 54 proteins were upregulated in S. pneumoniae grown in MDCM. It was also noted that several of the downregulated proteins were involved in cell energy metabolism, amino acid synthesis, and reduction of oxidation products. More importantly, several ATP-binding cassette transporters related to Fe uptake, such as PiuA, PiaA, PitA, and SPD_1609, were overexpressed for increased Fe uptake from the MDCM. The results suggest that Mn deficiency disturbs multiple metabolic processes in S. pneumoniae. Furthermore, it causes a compensatory effect of Fe for Mn, which is beneficial for the survival of the bacterium in extreme environments. SIGNIFICANCE: The relationship between manganese and iron metabolism in S. pneumoniae has not been clearly revealed. In this paper, we suggest that Mn limitation disturbs multiple metabolic processes and evidently decreases the ATP level in the bacterium. In order to survive in this extreme environment, bacteria upregulated three type of Fe ion transporters PiuABC (heme), PiaABC (ferrichrome) and PitABC (Fe3+) to uptake enough Fe ions to response to Mn deficiency. Therefore, this study reveals a bacterial mechanism of Fe compensation for Mn, and provides new insight for investigating the relativeness of Fe and Mn metabolism of bacteria.

Evolution and molecular mechanism of PitAs in iron transport of Streptococcus species.

Iron is an essential element for almost all bacteria. The iron ATP-binding cassette (ABC) transporters located on the cell membrane affects bacterial virulence and infection. Although a variety of Fe3+-transporters have been found in bacteria, their evolutionary processes are rarely studied. Pneumococcal iron ABC transporter (PitA), a highly conserved Fe3+-transporter in most pathogenic bacteria, influences the capsule formation and virulence of bacteria. However, multiple sequence alignment revealed that PitA is expressed in four different variants in bacteria, and the structural complexity of these variants increases progressively. To more efficiently import Fe3+ ions into bacterial cells, bacteria have evolved a fused PitA from two separately expressed PitA-1 (SPD_0227) and PitA-2 (SPD_0226) proteins. Further biochemical characterization indicated that both PitA-1 and PitA-2 have weaker Fe3+-binding ability than their protein complex. More importantly, Glutathione S-Transferase (GST) pull-down and isothermal titration calorimetry (ITC) detection showed that PitA-1 and PitA-2 interact with each other via Tyr111-Leu37, Asn112-Gln38, Asn103-Leu33, and Asn103-Thr34. Further molecular dynamics (MD) simulations demonstrated that this interaction in full-length PitA is stronger than that in the two individual proteins. Deletion of PitA family genes could lead to decrease in the ability of iron acquisition and of adhesion and invasion of S. pneumoniae. Our study revealed the evolving state and molecular mechanism of Fe3+-transporter PitAs in bacteria and provided important information for understanding the iron transportation mechanism in bacteria and designing new antibacterial drugs.

Comparative Proteomics of Streptococcus pneumoniae Response to Vancomycin Treatment.

Streptococcus pneumoniae is a gram-positive pathogen that causes otitis media, pneumonia, meningitis, and other serious diseases. Vancomycin is one of the most important drugs currently used for the treatment of gram-positive bacterial infections, representing, importantly, the last line of defense against bacteria that have developed resistance to other antibiotics. While primary efforts of most investigations focused on the antibacterial mechanism of vancomycin, few studies have been performed to assess the tolerance mechanism of bacteria to vancomycin. In this work, whole cellular proteins were extracted from S. pneumoniae D39 with or without vancomycin treatment. Subsequently, differentially expressed proteins (DEPs) were identified with two-dimensional gel electrophoresis coupled with matrix-assisted laser desorption/ionization mass spectrometry (MS)/MS. In total, 27 proteins were upregulated and four proteins were downregulated in vancomycin-treated S. pneumoniae. Gene ontology analysis indicated that these DEPs were mainly involved in the nucleic acid, protein, and carbohydrate biosynthetic processes. Verification experiments with real-time quantitative polymerase chain reaction showed that the gene expression profiles were consistent with proteomic data. These new observations may serve as a valuable resource for future investigations of vancomycin tolerance mechanisms of S. pneumoniae.

[Comparison among various software for LMS growth curve fitting methods].

OBJECTIVE: To explore the methods to realize the growth curve fitting of coefficients of skewness-median-coefficient of variation (LMS) using different software, and to optimize growth curve statistical method for grass-root child and adolescent staffs. METHODS: Regular physical examination data of head circumference for normal infants aging 3, 6, 9 and 12 months in Baotou City were analyzed. Statistical software such as SAS, R, STATA and SPSS were used to fit the LMS growth curve and the results were evaluated upon the user 's convenience, study circle, user interface, results display forms, software update and maintenance and so on. RESULTS: Growth curve fitting results showed the same calculation outcome and each of statistical software had its own advantages and disadvantages. With all the evaluation aspects in consideration, R software excelled others in LMS growth curve fitting. CONCLUSION: R software have the advantage over other software in grass roots child and adolescent staff.