TPP-Based Microfluidic Chip Design and Fabrication Method for Optimized Nerve Cells Directed Growth.

Microfluidic chips offer high customizability and excellent biocompatibility, holding important promise for the precise control of biological growth at the microscale. However, the microfluidic chips employed in the studies of regulating cell growth are typically fabricated through 2D photolithography. This approach partially restricts the diversity of cell growth platform designs and manufacturing efficiency. This paper presents a method for designing and manufacturing neural cell culture microfluidic chips (NCMC) using two-photon polymerization (TPP), where the discrete and directional cell growth is optimized through studying the associated geometric parameters of on-chip microchannels. This study involves simulations and discussions regarding the effects of different hatching distances on the mold surface topography and printing time in the Describe print preview module, which determines the appropriate printing accuracy corresponding to the desired mold structure. With the assistance of the 3D maskless lithography system, micron-level rapid printing of target molds with different dimensions were achieved. For NCMC with different geometric parameters, COMSOL software was used to simulate the local flow velocity and shear stress characteristics within the microchannels. SH-SY5Y cells were selected for directional differentiation experiments on NCMC with different geometric parameters. The results demonstrate that the TPP-based manufacturing method efficiently constructs neural microfluidic chips with high precision, optimizing the discrete and directional cell growth. We anticipate that our method for designing and manufacturing NCMC will hold great promise in construction and application of microscale 3D drug models.

Antimicrobial and anti-biofilm activity of a thiazolidinone derivative against Staphylococcus aureus in vitro and in vivo.

Staphylococcus aureus (S. aureus) causes many infections with significant morbidity and mortality. S. aureus can form biofilms, which can cause biofilm-associated diseases and increase resistance to many conventional antibiotics, resulting in chronic infection. It is critical to develop novel antibiotics against staphylococcal infections, particularly those that can kill cells embedded in biofilms. This study aimed to investigate the bacteriocidal and anti-biofilm activities of thiazolidinone derivative (TD-H2-A) against S. aureus. A total of 40 non-duplicate strains were collected, and the minimum inhibitory concentrations (MICs) of TD-H2-A were determined. The effect of TD-H2-A on established S. aureus mature biofilms was examined using a confocal laser scanning microscope (CLSM). The antibacterial effects of the compound on planktonic bacteria and bacteria in mature biofilms were investigated. Other characteristics, such as cytotoxicity and hemolytic activity, were researched. A mouse skin infection model was used, and a routine hematoxylin and eosin (H&E) staining was used for histological examination. The MIC values of TD-H2-A against the different S. aureus strains were 6.3-25.0 µg/mL. The 5 × MIC TD-H2-A killed almost all planktonic S. aureus USA300. The derivative was found to have strong bacteriocidal activity against cells in mature biofilms meanwhile having low cytotoxicity and hemolytic activity against Vero cells and human erythrocytes. TD-H2-A had a good bacteriocidal effect on S. aureus SA113-infected mice. In conclusion, TD-H2-A demonstrated good bacteriocidal and anti-biofilm activities against S. aureus, paving the way for the development of novel agents to combat biofilm infections and multidrug-resistant staphylococcal infections.IMPORTANCEStaphylococcus aureus, a notorious pathogen, can form a stubborn biofilm and develop drug resistance. It is crucial to develop new anti-infective therapies against biofilm-associated infections. The manuscript describes the new antibiotic to effectively combat multidrug-resistant and biofilm-associated diseases.

Changes in properties of human milk under different conditions of frozen storage.

Human milk is the best source of nutrition for infants. Lower freezing temperatures and faster freezing rates allow for better preservation of human milk. However, research on the freezing conditions of human milk is limited. This study investigated the effectiveness of quick freezing and suitable freezing conditions for home preservation. Human milk was stored under different freezing conditions (-18 °C, -18 °C quick freezing, -30 °C, -40 °C, -60 °C, and - 80 °C) for 30, 60, and 90 days and then evaluated for changes in the microbial counts, bioactive protein, and lipid. The results showed that the total aerobic bacterial and Bifidobacteria counts in human milk after storage at freezing temperatures of - 30 °C and lower were closer to those of fresh human milk compared to - 18 °C. Furthermore, the lysozyme loss, lipid hydrolysis degree, and volatile organic compound production were lower. However, -18 °C quick freezing storage was not markedly different from -18 °C in maintaining human milk quality. Based on the results, for household and environmental reasons, the recommended temperature for storing human milk is suggested as -30 °C.

Type-III-A structure of mycobacteria CRISPR-Csm complexes involving atypical crRNAs.

Tuberculosis (TB), a leading cause of mortality globally, is a chronic infectious disease caused by Mycobacterium tuberculosis that primarily infiltrates the lung. The mature crRNAs in M. tuberculosis transcribed from the Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR) locus exhibit an atypical structure featured with 5' and 3' repeat tags at both ends of the intact crRNA, in contrast to typical Type-III-A crRNAs that possess 5' repeat tags and partial crRNA sequences. However, this structural peculiarity particularly concerning the specific binding characteristics of the 3' repeat end within the mature crRNA within the Csm complex, has not been comprehensively elucidated. Here, our Mycobacteria CRISPR-Csm complexes structure represents the largest Csm complex reported to date. It incorporates an atypical Type-III-A CRISPR RNA (crRNA) (46 nt) with 5' 8-nt and 3' 4-nt repeat sequences in the stoichiometry of Mycobacteria Csm1125364151. The PAM-independent single-stranded RNAs (ssRNAs) are the most suitable substrate for the Csm complex. The 3'-repeat end trimming of mature crRNA was not necessary for its cleavage activity in Type-III-A Csm complex. Our work broadens our understanding of the Type-III-A Csm complex and identifies another mature crRNA processing mechanism in the Type-III-A CRISPR-Cas system based on structural biology.

Event-triggered hybrid impulsive control for synchronization of fractional-order multilayer signed networks under cyber attacks.

In this paper, we consider the exponential bipartite synchronization (EBS) problem of fractional-order multilayer signed networks with time-varying delays (FO-MSNT) under random cyber attacks. In contrast to the existing literature, the proposed hybrid event-triggered controller combines the advantages of feedback controller and impulsive controller, and the event-triggered condition is constructed by applying the network topology and the Lyapunov function of the subsystem, rather than the state function of the subsystem. Based on the Lyapunov-Razumikhin method and the graph theory, some sufficient conditions for achieving EBS of FO-MSNT under cyber attacks which are related to the topology of networks, the event-triggered parameters, the order of fractional derivative and the signal sent by the enemy are obtained. Furthermore, fractional-order coupled Chua's circuits model and fractional-order power systems built on MSNT are established and the EBS issues under cyber attacks are analyzed. Numerical examples and simulations are provided to show the validity of our theories.

ZmELF3.1 integrates the RA2-TSH4 module to repress maize tassel branching.

Tassel branch number (TBN) is a key agronomic trait for adapting to high-density planting and grain yield in maize. However, the molecular regulatory mechanisms underlying tassel branching are still largely unknown. Here, we used molecular and genetic studies together to show that ZmELF3.1 plays a critical role in regulating TBN in maize. Previous studies showed that ZmELF3.1 forms the evening complex through interacting with ZmELF4 and ZmLUX to regulate flowering in maize and that RA2 and TSH4 (ZmSBP2) suppresses and promotes TBN in maize, respectively. In this study, we show that loss-of-function mutants of ZmELF3.1 exhibit a significant increase of TBN. We also show that RA2 directly binds to the promoter of TSH4 and represses its expression, thus leading to reduced TBN. We further demonstrate that ZmELF3.1 directly interacts with both RA2 and ZmELF4.2 to form tri-protein complexes that further enhance the binding of RA2 to the promoter of TSH4, leading to suppressed TSH4 expression and consequently decreased TBN. Our combined results establish a novel functional link between the ELF3-ELF4-RA2 complex and miR156-SPL regulatory module in regulating tassel branching and provide a valuable target for genetic improvement of tassel branching in maize.

Analysis of preoperative computed tomography radiomics and clinical factors for predicting postsurgical recurrence of papillary thyroid carcinoma.

BACKGROUND: Postsurgical recurrence is of great concern for papillary thyroid carcinoma (PTC). We aim to investigate the value of computed tomography (CT)-based radiomics features and conventional clinical factors in predicting the recurrence of PTC. METHODS: Two-hundred and eighty patients with PTC were retrospectively enrolled and divided into training and validation cohorts at a 6:4 ratio. Recurrence was defined as cytology/pathology-proven disease or morphological evidence of lesions on imaging examinations within 5 years after surgery. Radiomics features were extracted from manually segmented tumor on CT images and were then selected using four different feature selection methods sequentially. Multivariate logistic regression analysis was conducted to identify clinical features associated with recurrence. Radiomics, clinical, and combined models were constructed separately using logistic regression (LR), support vector machine (SVM), k-nearest neighbor (KNN), and neural network (NN), respectively. Receiver operating characteristic analysis was performed to evaluate the model performance in predicting recurrence. A nomogram was established based on all relevant features, with its reliability and reproducibility verified using calibration curves and decision curve analysis (DCA). RESULTS: Eighty-nine patients with PTC experienced recurrence. A total of 1218 radiomics features were extracted from each segmentation. Five radiomics and six clinical features were related to recurrence. Among the 4 radiomics models, the LR-based and SVM-based radiomics models outperformed the NN-based radiomics model (P = 0.032 and 0.026, respectively). Among the 4 clinical models, only the difference between the area under the curve (AUC) of the LR-based and NN-based clinical model was statistically significant (P = 0.035). The combined models had higher AUCs than the corresponding radiomics and clinical models based on the same classifier, although most differences were not statistically significant. In the validation cohort, the combined models based on the LR, SVM, KNN, and NN classifiers had AUCs of 0.746, 0.754, 0.669, and 0.711, respectively. However, the AUCs of these combined models had no significant differences (all P > 0.05). Calibration curves and DCA indicated that the nomogram have potential clinical utility. CONCLUSIONS: The combined model may have potential for better prediction of PTC recurrence than radiomics and clinical models alone. Further testing with larger cohort may help reach statistical significance.

Psychodynamic-based virtual reality cognitive training system with personalized emotional arousal elements for mild cognitive impairment patients.

BACKGROUND AND OBJECTIVE: Mild cognitive impairment (MCI) is a serious threat to the physical health and quality of life of the elderly, as well as a heavy burden on families and society. The current computer-based rehabilitation training ignores the role of emotions in cognitive impairment rehabilitation, making it difficult to improve patient engagement and efficiency. To address this, a psychodynamics-based cognitive rehabilitation training method with personalized emotional arousal elements was proposed using virtual reality technology. METHODS: Our proposed method contains four training tasks, which cover (audiovisual memory, attention & processing, working memory, abstract & Logic, spatial pathfinding) and six positive emotional arousal elements (sensory feedback, achievement system, multiplayer interaction, score comparison, relaxation scenarios, and peaceful videos) to motivate participants to persist during cognitive training continuously and maintain a positive mental attitude toward training. The six emotional arousal elements were divided into two personalized combinations-full combination and half combination-based on the results of the pre-assessment and were dynamically distributed throughout both the training tasks and post-training. RESULTS: Fifteen participants with MCI were recruited to complete the proposed experiment and validate the effectiveness of the system. They were first asked to complete two assessments (e.g., the big five scale and the positive and negative affect scale) to investigate their personalities. Based on the results of the assessments, they were provided with a full or half combination of arousal elements in the training tasks and post-training. Finally, the acceptability of the system and task experience were assessed using questionnaires. Notably, there was a significant increase in training scores for participants who completed a six-week training period (66.7%, 33.4%, and 25.0% for attention and processing, working memory, and abstraction and logic, respectively). The results show that positive emotional arousal had a positive effect on the MCI participants. The training tasks and arousal elements can improve cognitive function and enhance the confidence and engagement of participants. There were no significant differences in cognitive domain training scores between the two groups. CONCLUSIONS: This personalized cognitive training system has the potential to serve as a convenient solution for complementary treatment of MCI.

Histogram analysis of quantitative parameters from synthetic MRI: correlations with prognostic factors in nasopharyngeal carcinoma.

OBJECTIVES: To evaluate the correlation between histogram parameters derived from synthetic magnetic resonance imaging (SyMRI) and prognostically relevant factors in nasopharyngeal carcinoma (NPC). METHODS: Fifty-nine consecutive NPC patients were prospectively enrolled. Quantitative parameters (T1, T2, and proton density (PD)) were obtained by outlining the three-dimensional volume of interest (VOI) of all lesions. Then, histogram analysis of these quantitative parameters was performed and the correlations with prognostically relevant factors were assessed. By choosing appropriate cutoff, we divided the sample into two groups. Independent-samples t test/Mann-Whitney U test was used and ROC curve analysis was further processed. RESULTS: Histogram parameters of the T1, T2, and PD maps were positively correlated with the Ki-67 expression levels, and PD_mean was the most representative parameter (AUC: 0.861). The PD map exhibited good performance in differentiating epidermal growth factor receptor (EGFR) expression levels (AUC: 0.706~0.732) and histological type (AUC: 0.650~0.660). T2_minimum was highest correlated with Epstein-Barr virus (EBV) DNA levels (r = - 0.419), and PD_75th percentile exhibited the highest performance in distinguishing positive and negative EBV DNA groups (AUC: 0.721). T1_minimum was statistically correlated with EA-IgA expression (r = - 0.313). Additionally, several histogram parameters were negatively correlated with tumor stage (T stage: r = - 0.259 ~ - 0.301; N stage: r = - 0.348 ~ - 0.456; clinical stage: r = - 0.419). CONCLUSIONS: Histogram parameters of SyMRI could reflect tissue intrinsic characteristics and showed potential value in assessing the Ki-67 and EGFR expression levels, histological type, EBV DNA level, EA-IgA, and tumor stage. KEY POINTS: • SyMRI combined with histogram analysis may help clinicians to assess different prognostic factor statuses in nasopharyngeal carcinoma. • The PD map exhibited good discriminating performance in the Ki-67 and EGFR expression levels. • Histogram parameters of SyMRI were negatively correlated with EBV-related blood biomarkers and TNM stage.

Pretreatment synthetic magnetic resonance imaging predicts disease progression in nonmetastatic nasopharyngeal carcinoma after intensity modulation radiation therapy.

BACKGROUND: To investigate the potential of synthetic MRI (SyMRI) in the prognostic assessment of patients with nonmetastatic nasopharyngeal carcinoma (NPC), and the predictive value when combined with diffusion-weighted imaging (DWI) as well as clinical factors. METHODS: Fifty-three NPC patients who underwent SyMRI were prospectively included. 10th Percentile, Mean, Kurtosis, and Skewness of T1, T2, and PD maps and ADC value were obtained from the primary tumor. Cox regression analysis was used for analyzing the association between SyMRI and DWI parameters and progression-free survival (PFS), and then age, sex, staging, and treatment as confounding factors were also included. C-index was obtained by bootstrap. Moreover, significant parameters were used to construct models in predicting 3-year disease progression. ROC curves and leave-one-out cross-validation were used to evaluate the performance and stability. RESULTS: Disease progression occurred in 16 (30.2%) patients at a follow-up of 39.6 (3.5, 48.2) months. T1_Kurtosis, T1_Skewness, T2_10th, PD_Mean, and ADC were correlated with PFS, and T1_Kurtosis (HR: 1.093) and ADC (HR: 1.009) were independent predictors of PFS. The C-index of SyMRI and SyMRI + DWI + Clinic models was 0.687 and 0.779. Moreover, the SyMRI + DWI + Clinic model predicted 3-year disease progression better than DWI or Clinic model (p ≤ 0.008). Interestingly, there was no significant difference between the SyMRI model (AUC: 0.748) and SyMRI + DWI + Clinic model (AUC: 0.846, p = 0.092). CONCLUSION: SyMRI combined with histogram analysis could predict disease progression in NPC patients, and SyMRI + DWI + Clinic model further improved the predictive performance.

Dynamics of a within-host drug resistance model with impulsive state feedback control.

Bacterial resistance poses a major hazard to human health, and is caused by the misuse and overuse of antibiotics. Thus, it is imperative to investigate the optimal dosing strategy to improve the treatment effect. In this study, a mathematical model of antibiotic-induced resistance is presented to improve the antibiotic effectiveness. First, conditions for the global asymptotical stability of the equilibrium without pulsed effect are given according to the Poincaré-Bendixson Theorem. Second, a mathematical model of the dosing strategy with impulsive state feedback control is also formulated to reduce drug resistance to an acceptable level. The existence and stability of the order-1 periodic solution of the system are discussed to obtain the optimal control of antibiotics. Finally, our conclusions are confirmed by means of numerical simulations.

Histogram analysis of synthetic magnetic resonance imaging: Correlations with histopathological factors in head and neck squamous cell carcinoma.

PURPOSE: To analyse the association between histogram parameters derived from synthetic MRI (SyMRI) and different histopathological factors in head and neck squamous cell carcinoma (HNSCC). METHOD: Sixty-one patients with histologically proven primary HNSCC were prospectively enrolled. The correlations between histogram parameters of SyMRI (T1, T2 and proton density (PD) maps) and histopathological factors were analysed using Spearman analysis. The Mann-Whitney U test or Student's t test was utilized to differentiate histological grades and human papillomavirus (HPV) status. The ROC curves and leave-one-out cross-validation (LOOCV) were used to evaluate the differentiation performance. Bootstrapping was applied to avoid overfitting. RESULTS: Several histogram parameters were associated with histological grade: T1 map (r = 0.291) and PD map (r = 0.294 - 0.382/-0.343), and PD_75th Percentile showed the highest differentiation performance (AUC: 0.721 (ROC) and 0.719 (LOOCV)). Moderately negative correlations were found between p16 status and the histogram parameters: T1 map (r = -0.587 - -0.390), T2 map (r = -0.649 - -0.357) and PD map (r = -0.537 - -0.338). In differentiating HPV infection, Entropy was the most discriminative parameter in each map and T2_Entropy showed the highest diagnostic performance (AUC: 0.851 [ROC] and 0.851 [LOOCV]). Additionally, several histogram parameters were correlated with Ki-67 (r = -0.379/-0.397), epidermal growth factor receptor (EGFR) (r = 0.318/0.322) status and p53 (r = 0.452 - 0.665/-0.607) status. CONCLUSIONS: Histogram parameters derived from SyMRI may serve as a potential biomarker for discriminating relevant histopathological features, including histological differentiation grade, HPV infection, Ki-67, EGFR and p53 statuses.

DHA-enriched phosphatidylserine alleviates high fat diet-induced jejunum injury in mice by modulating gut microbiota.

A long-term high-fat diet (HFD) is one of the high-risk factors for intestinal barrier damage. Docosahexaenoic acid-enriched phosphatidylserine (DHA-PS) has multiple biological activities, while its protective effect on HFD-caused jejunum injury remains unknown. Thus, the present study investigated the protective effect of DHA-PS on HFD-induced jejunum injury in mice. Our results showed that DHA-PS (100 mg per kg per d) could protect against HFD-caused jejunum injury by decreasing the levels of inflammatory factors such as interleukin (IL)-1ß, IL-6, and tumor necrosis factor-α (TNF-α) in the serum and jejunum tissues, with histological analysis confirming this injury amelioration. Additionally, DHA-PS alleviated the HFD-caused oxidative stress by decreasing malondialdehyde (MDA) and increasing total antioxidant capacity (T-AOC), superoxide dismutase (SOD), glutathione peroxidase (GSH-Px) and catalase (CAT) levels in the jejunum. Moreover, DHA-PS significantly increased the expression of tight junction proteins (ZO-1, occludin, and claudin-4) in the jejunum, and modulated the HFD-induced gut microbiota disorder by decreasing the Firmicutes and Bacteroidetes ratio, and reducing the relative abundance of Lachnoclostridium, Coriobacteriaceae, Desulfovibrionaceae, and Helicobacter, while increasing the relative abundance of Lachnospiraceae_NK4A136_group, Alistipes, norank_f__Muribaculaceae, and Bacteroides. Overall, these results support that DHA-PS can alleviate the HFD-caused jejunum injury.

The utility of texture analysis based on quantitative synthetic magnetic resonance imaging in nasopharyngeal carcinoma: a preliminary study.

BACKGROUND: Magnetic resonance imaging (MRI) is commonly used for the diagnosis of nasopharyngeal carcinoma (NPC) and occipital clivus (OC) invasion, but a proportion of lesions may be missed using non-enhanced MRI. The purpose of this study is to investigate the diagnostic performance of synthetic magnetic resonance imaging (SyMRI) in differentiating NPC from nasopharyngeal hyperplasia (NPH), as well as evaluating OC invasion. METHODS: Fifty-nine patients with NPC and 48 volunteers who underwent SyMRI examination were prospectively enrolled. Eighteen first-order features were extracted from VOIs (primary tumours, benign mucosa, and OC). Statistical comparisons were conducted between groups using the independent-samples t-test and the Mann-Whitney U test to select significant parameters. Multiple diagnostic models were then constructed using multivariate logistic analysis. The diagnostic performance of the models was calculated by receiver operating characteristics (ROC) curve analysis and compared using the DeLong test. Bootstrap and 5-folds cross-validation were applied to avoid overfitting. RESULTS: The T1, T2 and PD map-derived models had excellent diagnostic performance in the discrimination between NPC and NPH in volunteers, with area under the curves (AUCs) of 0.975, 0.972 and 0.986, respectively. Besides, SyMRI models also showed excellent performance in distinguishing OC invasion from non-invasion (AUC: 0.913-0.997). Notably, the T1 map-derived model showed the highest diagnostic performance with an AUC, sensitivity, specificity, and accuracy of 0.997, 96.9%, 97.9% and 97.5%, respectively. By using 5-folds cross-validation, the bias-corrected AUCs were 0.965-0.984 in discriminating NPC from NPH and 0.889-0.975 in discriminating OC invasion from OC non-invasion. CONCLUSIONS: SyMRI combined with first-order parameters showed excellent performance in differentiating NPC from NPH, as well as discriminating OC invasion from non-invasion.

Added value of histogram analysis of ADC in predicting radiation-induced temporal lobe injury of patients with nasopharyngeal carcinoma treated by intensity-modulated radiotherapy.

BACKGROUND: This study evaluated the predictive potential of histogram analysis derived from apparent diffusion coefficient (ADC) maps in radiation-induced temporal lobe injury (RTLI) of nasopharyngeal carcinoma (NPC) after intensity-modulated radiotherapy (IMRT). RESULTS: Pretreatment diffusion-weighted imaging (DWI) of the temporal lobes of 214 patients with NPC was retrospectively analyzed to obtain ADC histogram parameters. Of the 18 histogram parameters derived from ADC maps, 7 statistically significant variables in the univariate analysis were included in the multivariate logistic regression analysis. The final best prediction model selected by backward stepwise elimination with Akaike information criteria as the stopping rule included kurtosis, maximum energy, range, and total energy. A Rad-score was established by combining the four variables, and it provided areas under the curve (AUCs) of 0.95 (95% confidence interval [CI] 0.91-0.98) and 0.89 (95% CI 0.81-0.97) in the training and validation cohorts, respectively. The combined model, integrating the Rad-score with the T stage (p = 0.02), showed a favorable prediction performance in the training and validation cohorts (AUC = 0.96 and 0.87, respectively). The calibration curves showed a good agreement between the predicted and actual RTLI occurrences. CONCLUSIONS: Pretreatment histogram analysis of ADC maps and their combination with the T stage showed a satisfactory ability to predict RTLI in NPC after IMRT.

Development and validation of a prediction model of pneumothorax after CT-guided coaxial core needle lung biopsy.

Background: Pneumothorax is the most common complication of computed tomography-guided coaxial core needle biopsy (CCNB) and may be life-threatening. We aimed to evaluate the risk factors and develop a model for predicting pneumothorax in patients undergoing computed tomography-guided CCNB, and to further determine its clinical utility. Methods: Univariate and multivariate logistic regression analyses were conducted to identify independent risk factors for pneumothorax from 18 variables. A predictive model was established using multivariable logistic regression and presented as a nomogram based on a training cohort of 690 patients who underwent computed tomography-guided CCNB. The model was validated in 253 consecutive patients in the validation cohort and 250 patients in the test cohort. The area under the curve was used to determine the predictive accuracy of the proposed model. Results: The risk factors associated with pneumothorax after computed tomography-guided CCNB were sex, patient position, lung field, lesion contact with the pleura, lesion size, distance from the pleura to the lesion, presence of emphysema adjacent to the biopsy tract, and crossing fissures. The predictive model that incorporated these predictors showed good predictive performance in the training cohort [area under the curve, 0.71 (95% confidence interval: 0.67-0.75)], validation cohort [0.71 (0.64-0.78)], and internal test cohort [0.68 (0.60-0.75)]. The nomogram also provided excellent calibration and discrimination, and decision curve analysis (DCA) demonstrated its clinical utility. Conclusions: The predictive model showed good performance for pneumothorax after computed tomography-guided CCNB and may help improve individualized preoperative prediction.

Mutation of gdpS gene induces a viable but non-culturable state in Staphylococcus epidermidis and changes in the global transcriptional profile.

BACKGROUND: In the genome of staphylococci, only the gdpS gene encodes the conserved GGDEF domain, which is the characteristic of diguanylate cyclases. In our previous study, we have demonstrated that the gdpS gene can modulate biofilm formation by positively regulating the expression of ica operon in Staphylococcus epidermidis. Moreover, this regulation seems to be independent of the c-di-GMP signaling pathway and the protein-coding function of this gene. Therefore, the biological function of the gdpS gene remains to be further investigated. RESULTS: In the present study, it was observed that mutation of the gdpS gene induced S. epidermidis to enter into a presumed viable but nonculturable state (VBNC) after cryopreservation with glycerol. Similarly, when moved from liquid to solid culture medium, the gdpS mutant strain also exhibited a VBNC state. Compared with the wild-type strain, the gdpS mutant strain autolyzed more quickly during storage at 4℃, indicating its increased susceptibility to low temperature. Transcriptional profiling analysis showed that the gdpS mutation affected the transcription of 188 genes (92 genes were upregulated and 96 genes were downregulated). Specifically, genes responsible for glycerol metabolism were most markedly upregulated and most of the altered genes in the mutant strain are those involved in nitrogen metabolism. In addition, the most significantly downregulated genes included the betB gene, whose product catalyzes the synthesis of glycine betaine and confers tolerance to cold. CONCLUSION: The preliminary results suggest that the gdpS gene may participate in VBNC formation of S. epidermidis in face of adverse environmental factors, which is probably achieved by regulating expression of energy metabolism genes. Besides, the gdpS gene is critical for S. epidermidis to survive low temperature, and the underlying mechanism may be partly explained by its influence on expression of betB gene.

POMDP-Based Real-Time Path Planning for Manipulation of Multiple Microparticles via Optoelectronic Tweezers.

With high throughput and high flexibility, optoelectronic tweezers (OETs) hold huge potential for massively parallel micromanipulation. However, the trajectory of the virtual electrode has been planned in advance in most synchronous manipulations for multiple targets based on an optically induced dielectrophoresis (ODEP) mechanism, which is insufficient to ensure the stability and efficiency in an environment with potential collision risk. In this paper, a synchronously discretized manipulation method based on a centralized and decoupled path planner is proposed for transporting microparticles of different types with an OET platform. An approach based on the Kuhn-Munkres algorithm is utilized to achieve the goal assignment between target microparticles and goal positions. With the assistance of a visual feedback module, a path planning approach based on the POMDP algorithm dynamically determines the motion strategies of the particle movement to avoid potential collisions. The geometrical parameters of the virtual electrodes are optimized for different types of particles with the goal of maximum transport speed. The experiments of micropatterning with different morphologies and transporting multiple microparticles (e.g., polystyrene microspheres and 3T3 cells) to goal positions are performed. These results demonstrate that the proposed manipulation method based on optoelectronic tweezers is effective for multicell transport and promises to be used in biomedical manipulation tasks with high flexibility and efficiency.

Molecular characterization and virulence gene profiling of methicillin-resistant Staphylococcus aureus associated with bloodstream infections in southern China.

Methicillin-resistant Staphylococcus aureus (MRSA) causes an enormous illness burden, including skin and soft tissue infections (SSTIs), pneumonia, bloodstream infections (BSI), and sepsis. BSI are associated with significant patient morbidity and mortality worldwide. However, limited information is available on MRSA-related BSI in China. This study aimed to investigate the molecular characterization of 77 MRSA isolates recovered from hospitalized patients with BSI between 2012 and 2020 at three first-class tertiary hospitals in southern China based on multilocus sequence typing (MLST), spa typing, and staphylococcal cassette chromosome mec (SCCmec) typing. Overall, 13 clonal complexes (CCs) were identified, with CC59 and CC5 being the largest clusters, indicating high genetic diversity among BSI-causing MRSA isolates. ST59 was the most prevalent MLST type (22.1%). ST5/ST764-MRSA SCCmec II was the predominant adult MRSA clone, whereas ST59-MRSA SCCmec IV was the most common pediatric MRSA clone. ST5-t2460, ST764-t1084, and ST59-t437 were the most common types of adult MRSA isolates, whereas ST59-t437 and ST59-t172 were the predominant types of children's MRSA isolates. ST59-SCCmec IV/V represented the most common clone among community acquired-MRSA isolates. ST5/ST764-SCCmec II was the most common type of hospital-associated MRSA isolate. The most prevalent toxin-encoding genes detected were hla, hld, icaA, and clfA (96.1-100%). Forty-three (100%, 43/43) isolates harbored more than 18 of the tested virulence genes in adults and eight virulence genes (23.5%, 8/34) in children. Virulence gene analysis revealed diversity among different clones: the positivity rates for the Panton-Valentine leukocidin (PVL) gene were 55.8 and 35.3% in adult and pediatric MRSA isolates, respectively; the genes seb-sei were present in all adult strains; seb-seg-sei-seo were present in all ST5, ST59, ST15, ST45, and ST22 adult strains; and seg-sei-sem-sen-seo were present in different clones, including ST15, ST45, and ST22 adult MRSA isolates and ST25, ST30, ST546, and ST72 children's MRSA isolates. Adult MRSA isolates had significantly higher antibiotic resistance rates and virulence gene prevalence than pediatric MRSA isolates. For 8 years, this study provided epidemiological data on the molecular characteristics and virulence genes in different groups of MRSA BSI in China. Our findings may provide critical information for a better understanding of MRSA BSI.

Prediction model based on preoperative CT findings for carotid artery invasion in patients with head and neck masses.

Objectives: To investigate the performance of a model in predicting carotid artery (CA) invasion in patients with head and neck masses using computed tomography (CT). Methods: This retrospective study included patients with head and neck masses who underwent CT and surgery between January 2013 and July 2021. Patient characteristics and ten CT features were assessed by two radiologists. The patients were randomly allocated to a training cohort (n=106) and a validation cohort (n=109). Independent risk factors for CA invasion were assessed by univariate and multivariate logistic regression analyses. The predictive model was established as a nomogram using the training cohort. In addition, the calibration, discrimination, reclassification, and clinical application of the model were assessed in the validation cohort. Results: A total of 215 patients were evaluated, including 54 patients with CA invasion. Vascular wall deformation (odds ratio [OR], 7.17; p=0.02) and the extent of encasement to the CA (OR, 1.02; p<0.001) were independent predictors of CA invasion in the multivariable analysis in the training cohort. The performance of the model was similar between the training and validation cohort, with an area under the receiver operating characteristic curve of 0.93 (95% confidence intervals [CI], 0.88-0.98) and 0.88 (95% CI, 0.80-0.96) (p=0.07), respectively. The calibration curve showed a good agreement between the predicted and actual probabilities. Conclusion: A predictive model for carotid artery invasion can be defined based on features that come from patient characteristics and CT data to help in improve surgical planning and invasion evaluation.