Suberoylanilide hydroxamic acid attenuates cognitive impairment in offspring caused by maternal surgery during mid-pregnancy.

Some pregnant women have to experience non-obstetric surgery during pregnancy under general anesthesia. Our previous studies showed that maternal exposure to sevoflurane, isoflurane, propofol, and ketamine causes cognitive deficits in offspring. Histone acetylation has been implicated in synaptic plasticity. Propofol is commonly used in non-obstetric procedures on pregnant women. Previous studies in our laboratory showed that maternal propofol exposure in pregnancy impairs learning and memory in offspring by disturbing histone acetylation. The present study aims to investigate whether HDAC inhibitor suberoylanilide hydroxamic acid (SAHA) could attenuate learning and memory deficits in offspring caused by maternal surgery under propofol anesthesia during mid-pregnancy. Maternal rats were exposed to propofol or underwent abdominal surgery under propofol anesthesia during middle pregnancy. The learning and memory abilities of the offspring rats were assessed using the Morris water maze (MWM) test. The protein levels of histone deacetylase 2 (HDAC2), phosphorylated cAMP response-element binding (p-CREB), brain-derived neurotrophic factor (BDNF), and phosphorylated tyrosine kinase B (p-TrkB) in the hippocampus of the offspring rats were evaluated by immunofluorescence staining and western blot. Hippocampal neuroapoptosis was detected by TUNEL staining. Our results showed that maternal propofol exposure during middle pregnancy impaired the water-maze learning and memory of the offspring rats, increased the protein level of HDAC2 and reduced the protein levels of p-CREB, BDNF and p-TrkB in the hippocampus of the offspring, and such effects were exacerbated by surgery. SAHA alleviated the cognitive dysfunction and rescued the changes in the protein levels of p-CREB, BDNF and p-TrkB induced by maternal propofol exposure alone or maternal propofol exposure plus surgery. Therefore, SAHA could be a potential and promising agent for treating the learning and memory deficits in offspring caused by maternal nonobstetric surgery under propofol anesthesia.

Structural Diversity Design, Four Nucleation Methods Growth and Mechanism of 3D Hollow Box TiO2 Nanocrystals with a Temperature-Controlled High (001) Crystal Facets Exposure Ratio.

Three-dimensional (3D) hollow box TiO2 nanocrystals with structural diversity have been designed and grown by four nucleation methods, including the acid dissolution denucleation method with Fe2O3 as heterogeneous nucleation, the topological phase transition method, the sonic solvothermal method, and the air atmosphere sintering method with TiOF2 as homogeneous nucleation. Through full morphology analysis and structural characterization, reasonable growth mechanisms of 3D hollow box TiO2 nanocrystals were proposed, including nucleation dissolution, Oswald ripening, and hydrolysis reactions. It was found that the high energy (001) crystal facets exposure ratio was closely correlated with reaction temperature of four nucleation-methods, which even reached 92% for the first time. Under simulated sunlight irradiation, their hydrogen production performance and photocatalytic degradation efficiency on model dye molecules rhodamine B (RhB) and methylene blue (MB) were evaluated, and as-prepared hollow box TiO2 nanocrystals prepared by the sonic solvothermal method exhibited the best photocatalytic performance, with a hydrogen production rate of 93.88 µmol/g/h. Within 70 min, the photocatalytic degradation rates of RhB and MB reached 96.59 and 75.25%, respectively, which were 5.74 and 5.54 times that of P25. Their properties are closely connected with the orderly cubic and hierarchy configuration structure of hollow box TiO2 nanocrystals, which have a high exposure ratio of (001) facet controlled by reaction temperatures, thereby greatly improving the photocatalytic activity. This study provides a classic reference for improving the properties of hollow box TiO2 nanocrystals through structural diversity design and various methods of nanocrystal growth.

Cellular crosstalk of macrophages and therapeutic implications in non-small cell lung cancer revealed by integrative inference of single-cell transcriptomics.

Introduction: Non-small cell lung cancer (NSCLC) exhibits heterogeneity with diverse immune cell infiltration patterns that can influence tumor cell behavior and immunotherapy. A comprehensive characterization of the tumor microenvironment can guide precision medicine. Methods: Here, we generated a single-cell atlas of 398170 cells from 52 NSCLC patients, and investigated the imprinted genes and cellular crosstalk for macrophages. Subsequently, we evaluated the effect of tumor cells on macrophages and verified the expression of marker genes using co-culture experiments, flow cytometry and RT-qPCR assays. Results: Remarkable macrophage adaptability to NSCLC environment was observed, which contributed to generating tumor-associated macrophages (TAMs). We identified 5 distinct functional TAM subtypes, of which the majority were SELENOP-positive macrophages, with high levels of SLC40A1 and CCL13. The TAMs were also involved in mediating CD8+ T cell activity and form intercellular interaction with cancer cells, as indicated by receptor-ligand binding. Indirect coculture of tumor cells SPC-A1 and THP-1 monocytes, produced M2-like TAMs that highly expressed several markers of SELENOP-positive macrophages. The abundance of this type TAMs seemed to be associated with poorer overall survival rates [hazard ratio (HR) = 1.34, 95% confidence interval (CI) = 0.98-1.83, p = 0.068] based on deconvolution of TCGA-LUAD dataset. Discussion: In summary, we provided a high-resolution molecular resource of TAMs, and displayed the acquired properties in the tumor microenvironment. Dynamic crosstalk between TAMs and tumor cells via multiple ligand-receptor pairs were revealed, emphasizing its role in sustaining the pro-tumoral microenvironment and its implications for cancer therapy.

Rare primary pulmonary mucosa-associated lymphoid tissue lymphoma misdiagnosed with tuberculosis: A case report.

RATIONALE: Primary pulmonary mucosa-associated lymphoid tissue lymphoma (MALToma) is a rare subtype of non-Hodgkin lymphoma with a relatively low incidence rate clinically. Atypical clinical symptoms and nonspecific chest computed tomography features of the disease make it difficult to determine and treatment is delayed. We discuss the diagnosis and treatment of a patient with primary pulmonary MALToma to raise clinicians' awareness of this condition. PATIENT CONCERNS: A 66-year-old male patient with a medical history of tuberculosis has been experiencing progressive exacerbation of respiratory symptoms and nonresponsive treatment without an unclear diagnosis for 5 years. He was transferred to our hospital because a nonspecific soft tissue mass in the right upper lobe of the lung was found on his chest computed tomography. Laboratory results with serum immunofixation electrophoresis showed polyclonal immunoglobulin (Ig) G, IgM, IgA, and λ-light chain on admission. DIAGNOSIS: Pathological examination and immunohistochemical staining of lung biopsy revealed a definitive diagnosis of pulmonary MALToma with stage IV. INTERVENTIONS AND OUTCOMES: The patient received immunotherapy with anti-CD20 monoclonal antibody (rituximab), and showed significant clinical improvement at the 6-month follow-up. CONCLUSIONS AND LESSONS: Diagnosis of primary pulmonary MALToma mainly relies on histopathological examination, and comprehensive laboratory examinations are also necessary. Clinicians should combine laboratory tests (such as immunofixation electrophoresis in our case) to assist in medical diagnosis in cases of atypical clinical manifestations and imaging characteristics. Immunotherapy appears to be the main treatment protocol for advanced patients.

Clinical Characteristics of Severe COVID-19 Patients During Omicron Epidemic and a Nomogram Model Integrating Cell-Free DNA for Predicting Mortality: A Retrospective Analysis.

Objective: This study aimed to investigate the clinical characteristics and risk factors of death in severe coronavirus disease 2019 (COVID-19) during the epidemic of Omicron variants, assess the clinical value of plasma cell-free DNA (cfDNA), and construct a prediction nomogram for patient mortality. Methods: The study included 282 patients with severe COVID-19 from December 2022 to January 2023. Patients were divided into survival and death groups based on 60-day prognosis. We compared the clinical characteristics, traditional laboratory indicators, and cfDNA concentrations at admission of the two groups. Univariate and multivariate logistic analyses were performed to identify independent risk factors for death in patients with severe COVID-19. A prediction nomogram for patient mortality was constructed using R software, and an internal validation was performed. Results: The median age of the patients included was 80.0 (71.0, 86.0) years, and 67.7% (191/282) were male. The mortality rate was 55.7% (157/282). Age, tracheal intubation, shock, cfDNA, and urea nitrogen (BUN) were the independent risk factors for death in patients with severe COVID-19, and the area under the curve (AUC) for cfDNA in predicting patient mortality was 0.805 (95% confidence interval [CI]: 0.713-0.898, sensitivity 81.4%, specificity 75.6%, and cut-off value 97.67 ng/mL). These factors were used to construct a prediction nomogram for patient mortality (AUC = 0.856, 95% CI: 0.814-0.899, sensitivity 78.3%, and specificity 78.4%), C-index was 0.856 (95% CI: 0.832-0.918), mean absolute error of the calibration curve was 0.007 between actual and predicted probabilities, and Hosmer-Lemeshow test showed no statistical difference (χ2=6.085, P=0.638). Conclusion: There was a high mortality rate among patients with severe COVID-19. cfDNA levels ≥97.67 ng/mg can significantly increase mortality. When predicting mortality in patients with severe COVID-19, a nomogram based on age, tracheal intubation, shock, cfDNA, and BUN showed high accuracy and consistency.

Highly sensitive and selective detection of nitrite using a fiber optofluidic laser.

Nitrite ion (NO2-) is a common contaminant that can significantly threaten human health and the environment. In this study, we demonstrate a chemical sensing platform to monitor the nitrite concentration using a fiber optofluidic laser (FOFL). An optical fiber, integrated into a microchannel, is used both as an optical micro-cavity and the sensing element. Rhodamine 6 G (Rh6G) in an aqueous micellar solution is used as the laser gain medium. The light intensity change of the lasing spectra is employed as an indicator for the NO2- ion concentration sensing. The lasing properties under different NO2- ion concentrations are experimentally and theoretically investigated to examine the sensing performance of the FOFL. The results show that the limit detection of the FOFL sensor is 0.54 µM, which is 2-order-of-magnitude lower than fluorescence measurement. The sensing mechanism of Rh6G for NO2- detection is studied by using density functional theory (DFT). The calculation results indicate that nitrite influences the electronic distribution of Rh6G based on the heavy atom effect, which leads to the fluorescence quenching of Rh6G in the excited state. In addition, the detection system exhibits favorable selectivity for NO2- ions.

Clinical data analysis of 86 patients with invasive infections caused by Malassezia furfur from a tertiary medical center and 37 studies.

Objective: Malassezia furfur (M. furfur) is a lipophilic, conditionally pathogenic yeast that mainly causes skin infections, but the reports of related invasive infections are increasing. The aim of this study is to provide clinical data to assist physicians in the management of patients with invasive infections caused by M. furfur. Methods: A case of pulmonary infection caused by M. furfur in a hematopoietic stem cell transplant patient for aplastic anemia was reported. In addition, the literature on invasive infection by M. furfur published in PubMed and Web of Science in English until 31 July 2022 was reviewed. Results: Clinical data analysis of 86 patients (from 37 studies and our case) revealed that most of them were preterm (44.2%), followed by adults (31.4%). M. furfur fungemia occurred in 79.1% of the 86 patients, and 45 of them were clearly obtained from catheter blood. Other patients developed catheter-related infections, pneumonia, peripheral thromboembolism, endocarditis, meningitis, peritonitis and disseminated infections. Thirty-eight preterm infants had underlying diseases such as very low birth weight and/or multiple organ hypoplasia. The remaining patients had compromised immunity or severe gastrointestinal diseases. 97.7% of patients underwent invasive procedures and 80.2% received total parenteral nutrition (TPN). Fever, thrombocytopenia and leukocytosis accounted for 55.8%, 38.4% and 24.4% of patients with M. furfur invasive infections, respectively. 69.8% of the patients received antifungal therapy, mainly amphotericin B (AmB) or azoles. Of 84 patients with indwelling catheters, 58.3% underwent the removal of catheters. TPN were discontinued in 30 of 69 patients. The all-cause mortality of 86 patients was 27.9%. Conclusions: M. furfur can cause a variety of invasive infections. These patients mostly occur in premature infants, low immunity and severe gastrointestinal diseases. Indwelling catheters and TPN infusion are major risk factors. AmB, l-AmB and azoles are the most commonly used agents, and simultaneous removal of the catheter and termination of TPN infusion are important for the treatment of M. furfur invasive infections.

Effects of Palladium Precursors on the Activity of Palladium Nanocatalysts for the Oxidation of Volatile Organic Components.

To screen a suitable precursor, the effects of palladium salts on performance of Pd nanocatalysts for the oxidation of volatile organic components (VOCs) were investigated. A series of catalysts was prepared by impregnating Pd(NO3)2, PdCl2 and Pd(NH3)4Cl2 on alumina-coated cordierites. These catalysts were characterized by XRF, ICP-OES, XRD, N2 adsorption-desorption, TEM, EDS, Raman spectroscopy, pulse-CO chemisorption, H2-TPR, NH3-TPD, and XPS. Pulse-CO chemisorption and TEM showed that Pd species formed by Pd(NO3)2 have the highest metal dispersion (17.7%), while the other two were aggregating. For the same Pd loading, the higher the metal dispersion, the more the number of PdO species, so the number of PdO particles in the catalyst prepared from Pd (NO3) 2 is the largest. The catalytic oxidation activities of these catalysts were evaluated by ethane and propane. Based on a 99% conversion in the oxidation of ethane and propane at 598 K and 583 K, respectively, the catalyst prepared from Pd(NO3)2 was considered to be the best performing catalyst. The chloride species in precursors can promote the aggregation of Pd species and poison the catalysts. The results show that Pd(NO3)2 is more suitable as the precursor of VOC oxidation catalyst than PdCl2 and Pd(NH3)4Cl2.

Approximate solutions to several classes of Volterra and Fredholm integral equations using the neural network algorithm based on the sine-cosine basis function and extreme learning machine.

In this study, we investigate a new neural network method to solve Volterra and Fredholm integral equations based on the sine-cosine basis function and extreme learning machine (ELM) algorithm. Considering the ELM algorithm, sine-cosine basis functions, and several classes of integral equations, the improved model is designed. The novel neural network model consists of an input layer, a hidden layer, and an output layer, in which the hidden layer is eliminated by utilizing the sine-cosine basis function. Meanwhile, by using the characteristics of the ELM algorithm that the hidden layer biases and the input weights of the input and hidden layers are fully automatically implemented without iterative tuning, we can greatly reduce the model complexity and improve the calculation speed. Furthermore, the problem of finding network parameters is converted into solving a set of linear equations. One advantage of this method is that not only we can obtain good numerical solutions for the first- and second-kind Volterra integral equations but also we can obtain acceptable solutions for the first- and second-kind Fredholm integral equations and Volterra-Fredholm integral equations. Another advantage is that the improved algorithm provides the approximate solution of several kinds of linear integral equations in closed form (i.e., continuous and differentiable). Thus, we can obtain the solution at any point. Several numerical experiments are performed to solve various types of integral equations for illustrating the reliability and efficiency of the proposed method. Experimental results verify that the proposed method can achieve a very high accuracy and strong generalization ability.

Self-focusing and self-splitting properties of partially coherent temporal pulses propagating in dispersive media.

Based on the coherence theory for non-stationary optical fields, we introduce a new class of partially coherent pulse sources with multi-cosine-Gaussian correlated Schell-model (MCGCSM) and derive the analytic expression for the temporally mutual coherence function (TMCF) of an MCGCSM pulse beam when it propagates through dispersive media. The temporally average intensity (TAI) and the temporal degree of coherence (TDOC) of the MCGCSM pulse beams spreading in dispersive media are investigated numerically, respectively. Our results show that over propagation distance, the evolution of pulse beams is from the primary single beam into multiple subpulses or form flat-topped TAI distributions by controlling source parameters. Moreover, when the chirp coefficient s < 0, the MCGCSM pulse beams through dispersive media will show the characteristics of two self-focusing processes. The reason why there are two self-focusing processes is explained from the perspective of physical meaning. The results in this paper can open the applications of pulse beams in multiple pulse shaping and laser micromachining and material processing.

An integrated solution of deep reinforcement learning for automatic IMRT treatment planning in non-small-cell lung cancer.

Purpose: To develop and evaluate an integrated solution for automatic intensity-modulated radiation therapy (IMRT) planning in non-small-cell lung cancer (NSCLC) cases. Methods: A novel algorithm named as multi-objectives adjustment policy network (MOAPN) was proposed and trained to learn how to adjust multiple optimization objectives in commercial Eclipse treatment planning system (TPS), based on the multi-agent deep reinforcement learning (DRL) scheme. Furthermore, a three-dimensional (3D) dose prediction module was developed to generate the patient-specific initial optimization objectives to reduce the overall exploration space during MOAPN training. 114 previously treated NSCLC cases suitable for stereotactic body radiotherapy (SBRT) were selected from the clinical database. 87 cases were used for the model training, and the remaining 27 cases for evaluating the feasibility and effectiveness of MOAPN in automatic treatment planning. Results: For all tested cases, the average number of adjustment steps was 21 ± 5.9 (mean ± 1 standard deviation). Compared with the MOAPN initial plans, the actual dose of chest wall, spinal cord, heart, lung (affected side), esophagus and bronchus in the MOAPN final plans reduced by 14.5%, 11.6%, 4.7%, 16.7%, 1.6% and 7.7%, respectively. The dose result of OARs in the MOAPN final plans was similar to those in the clinical plans. The complete automatic treatment plan for a new case was generated based on the integrated solution, with about 5-6 min. Conclusion: We successfully developed an integrated solution for automatic treatment planning. Using the 3D dose prediction module to obtain the patient-specific optimization objectives, MOAPN formed action-value policy can simultaneously adjust multiple objectives to obtain a high-quality plan in a shorter time. This integrated solution contributes to improving the efficiency of the overall planning workflow and reducing the variation of plan quality in different regions and treatment centers. Although improvement is warranted, this proof-of-concept study has demonstrated the feasibility of this integrated solution in automatic treatment planning based on the Eclipse TPS.

Fluorescent property of carbon dots extracted from cigarette smoke and the application in bio-imaging.

Cigarette smoke is one of the six major pollution sources in the room air. It contains large number of particles with size less than 10 nm. There exist carbon dots (CDs) in cigarette smoke which have strong fluorescence and with good bio-compatibility and low toxicity. CDs in cigarette smoke can be applied in bio-imaging which has great potential applications in the integration of cancer diagnosis and treatment. In this paper, CDs were extracted from cigarette smoke. Then, sodium borohydride was added to CDs aqueous solution for reduction and the reduced CDs (R-CDs) were used for biological cell imaging. The results indicate that the CDs with the particle size <10 nm in cigarette smoke are self-assembled by the polymerizated polycyclic aromatic hydrocarbons (PAHs) and ammonium nitrite which are disk nano-structure composed of sp2/sp3 carbon and oxygen/nitrogen groups or polymers. Sodium borohydride can reduce the carbonyl group on the surface of CDs to hydroxyl group and increase the ratio of the Na 1s ratio of the CDs from 1.86 to 7.42. The CDs can emit blue fluorescence under ultraviolet irradiation. After reduction, the R-CDS have the intensity of fluorescence 7.2 times than before and the fluorescence quantum yield increase from 6.13% to 8.86%. The photoluminescence (PL) wavelength of R-CDS have red-shift of 7 nm which was due to the increasing of Na element ratio. The onion epidermal cells labeled with R-CDs show that the CDs could pass through the cell wall into the cell and reach the nucleus. The cell wall and the nucleus could be clearly visualized. CDs also shows low toxicity to human bronchial epithelial cells (BEAS-2B) with good biological activity. The obtained results indicate that the CDs and R-CDs have good fluorescent property which could be used as bio-imaging agent.

Clinical Characteristics and Risk Factors for in-Hospital Mortality in 240 Cases of Infective Endocarditis in a Tertiary Hospital in China: A Retrospective Study.

Purpose: This study aimed (i) to investigate the clinical characteristics and risk factors related to in-hospital mortality in patients with infective endocarditis (IE) and (ii) to compare the differences in three age groups. Methods: A total of 240 IE cases diagnosed using the modified Duke criteria between January 2016 and December 2019 were included and retrospectively studied. Patients were stratified into three age groups: < 50 y, 50-65 y, and > 65 y. Results: The mean age of the patients was 51 ± 14 y, and 154 patients (64.2%) were male. In addition, 136 (56.7%) patients with IE had no previous cardiac disease. Congenital heart disease (CHD, 21.3%) was the most common underlying heart disease, followed by rheumatic heart disease (RHD, 8.8%). Streptococcus was found in 55 (22.9%) patients and was the most common causative pathogen, comprising 52.9% of all positive blood cultures. Echocardiography showed the presence of vegetations in 88.3% of cases and the predominant involvement of the left heart valves. Fever and cardiac murmur were the most frequent presentations, with no significant differences among age groups. Compared with younger patients, elderly patients had a lower operation rate and higher in-hospital mortality. The independent risk factors of in-hospital mortality were age > 65 y, intracranial infection, splenic embolization, cerebral hemorrhage, NYHA class III-IV, and prosthetic valve infection. Conclusion: CHD replaces RHD as the most common underlying heart disease in IE patients. Patients without previous cardiac disease are at increased risk of IE. Streptococcus is still the primary causative pathogen of IE. Elderly patients present with more comorbidities and complications, in addition to a more severe prognosis than younger patients. Age older than 65 y, intracranial infection, splenic embolization, cerebral hemorrhage, NYHA class III-IV, and prosthetic valve infection showed poorer in-hospital outcomes.

Extension of the Virtual Cell Based Assay from a 2-D to a 3-D Cell Culture Model.

Prediction of chemical toxicity is very useful in risk assessment. With the current paradigm shift towards the use of in vitro and in silico systems, we present herein a theoretical mathematical description of a quasi-diffusion process to predict chemical concentrations in 3-D spheroid cell cultures. By extending a 2-D Virtual Cell Based Assay (VCBA) model into a 3-D spheroid cell model, we assume that cells are arranged in a series of concentric layers within the sphere. We formulate the chemical quasi-diffusion process by simplifying the spheroid with respect to the number of cells in each layer. The system was calibrated and tested with acetaminophen (APAP). Simulated predictions of APAP toxicity were compared with empirical data from in vitro measurements by using a 3-D spheroid model. The results of this first attempt to extend the VCBA model are promising - they show that the VCBA model simulates close correlation between the influence of compound concentration and the viability of the HepaRG 3-D cell culture. The 3-D VCBA model provides a complement to current in vitro procedures to refine experimental setups, to fill data gaps and help in the interpretation of in vitro data for the purposes of risk assessment.

Septic Shock, Renal Abscess, and Bacteremia Due to Peptoniphilus asaccharolyticus in a Woman with Nephrosis and Diabetes Mellitus: Case Report and Literature Review.

Peptoniphilus asaccharolyticus is a Gram-positive anaerobic coccus, which forms part of the normal flora and the human commensals of the skin, genitourinary system, and gut. It can cause opportunistic infections in immunocompromised patients and is frequently isolated as part of polymicrobial spectra. Severe monomicrobial infections caused by the genus rarely occur. In this study, we report on septic shock, renal abscess, and bacteremia due to P. asaccharolyticus in a woman with nephrosis and diabetes mellitus. To the best of our knowledge, this report is the first to describe P. asaccharolyticus isolated from both renal abscess and blood cultures purely. The underlying diseases of the host and the removal of the double J tube were significant predisposing factors in this infection.

Cutaneous Protothecosis with Meningitis Due to Prototheca wickerhamii in an Immunocompetent Teenager: Case Report and Literature Review.

Human protothecosis is a rare infection caused by Prototheca spp., which are environmental achloric algae ubiquitously existing in nature. Members of the genus of Prototheca usually cause localized infection that affects the skin or wounds. Systemic infection is extremely rare and tends to occur in immunocompromised patients. Here, we report a case of cutaneous protothecosis and meningitis due to Prototheca wickerhamii in an immunocompetent teenager who obtained full-body tattoos at the time of infection. To the best of our knowledge, this is the first description of P. wickerhamii isolated from both skin tissue and cerebrospinal fluid. The data contained in this report will increase our understanding of this pathogen and elucidate the most optimal treatment.

Characterization of Carbapenem-Resistant Klebsiella pneumoniae ST15 Clone Coproducing KPC-2, CTX-M-15 and SHV-28 Spread in an Intensive Care Unit of a Tertiary Hospital.

OBJECTIVE: Nosocomial infection caused by carbapenem-resistant Klebsiella pneumoniae (CRKP) is a great threat to severely ill patients. Here we report an outbreak of K. pneumoniae ST15 isolates co-producing KPC-2, CTX-M-15, and SHV-28 in the cardiac surgery intensive care unit (CSICU) of a tertiary hospital. MATERIALS AND METHODS: From November 2019 to August 2020, all non-duplicated CRKP isolates were collected from the CSICU. The VITEK-2 compact system was used for bacterial identification and antimicrobial susceptibility testing. Clinical data were retrieved from electronic case records. All strains were also subjected to antibiotic resistance genes detection. Clonal relationships were analyzed by multilocus sequence typing (MLST) and pulsed-field gel electrophoresis (PFGE). RESULTS: A total of 28 non-duplicated CRKP isolates were collected, including 23 strains belonging to ST15 and 5 strains belonging to ST11. All ST15 isolates were susceptible to amikacin, tigecycline, polymyxin B and ceftazidime/avibactam, but resistant to carbapenems, cephalosporins, quinolones, tobramycin and gentamicin. The detection of resistant determinants showed that 21 strains of ST15 CRKP co-harboured blaKPC-2, blaCTX-M-15, blaSHV-28, blaTEM-1, blaOXA-1 and aac(6')-Ib-cr. All the 28 CRKP isolates were classified into five PFGE patterns (A, B, C, D and E), of which type A and B belonged to ST15 and type C, D and E belonged to ST11. PFGE type A was the predominant clonotype of this nosocomial infection and belonged to ST15. CONCLUSION: K. pneumoniae ST15 co-producing KPC-2, CTX-M-15, SHV-28, TEM-1, OXA-1 and aac(6')-Ib-cr is the predominant clone spread in the CSICU. Surveillance and comprehensive infection control measures should be strengthened in clinical practice.

Investigating the Efficacy and Safety of Thalidomide for Treating Patients With ß-Thalassemia: A Meta-Analysis.

At present, the main therapies for ß-thalassemia patients include regular blood transfusion and iron chelation, associating with a number of limitations. Thalidomide, a fetal hemoglobin (HbF) inducer that promotes γ-globin gene expression, has been reported to be effective for ß-thalassemia. Thus, this meta-analysis was conducted to assess the efficacy and safety of thalidomide for treating patients with ß-thalassemia. We searched the related studies from eight databases published from inception until December 1, 2021. The R 4.0.5 language programming was used to perform meta-analysis. After screening of retrieved articles, 12 articles were included that enrolled a total of 451 patients. The Cochrane Collaboration risk assessment tool was used to evaluate the quality and the bias risk of the randomized controlled trials (RCTs), and non randomized trials were assessed using Newcastle-Ottawa Scale (NOS). After treatment with thalidomide, the pooled overall response rate (ORR) was 85% (95% confidence interval (CI): 80-90%), and the pooled complete response rate (CRR) was 54% (95% confidence interval: 31-76%). Compared with the placebo group, the thalidomide group had higher odds of overall response rate (odds ratio = 20.4; 95% CI: 6.75-61.64) and complete response rate (odds ratio = 20.4; 95% CI: 6.75-61.64). A statistically significant increase in hemoglobin level and HbF level after treatment, while there was no statistically significant difference in adult hemoglobin (HbA) level, spleen size, and serum ferritin. According to the results of ORR and CRR, transfusion-dependent thalassemia (TDT) patients showed remarkable efficacy of thalidomide, 83 and 52% respectively. So we analyzed 30 transfusion-dependent thalassemia patients from three studies and found that the most frequent ß-globin gene mutations were CD41-42 (-TCTT), while response to thalidomide did not show any statistically significant relationship with XmnI polymorphism or CD41-42 (-TCTT) mutation. About 30% of patients experienced mild adverse effects of thalidomide. Collectively, thalidomide is a relatively safe and effective therapy to reduce the blood transfusion requirements and to increase Hb level in patients with ß-thalassemia.

Propagation characteristics of the perfect vortex beam in anisotropic oceanic turbulence.

The propagation model of orbital angular momentum (OAM) modes carried by the perfect vortex (pv) beam through anisotropic oceanic turbulence links is established and the factors influencing the OAM propagation are discussed. The findings show that the self-focusing property of pv beams is beneficial to the propagation of OAM modes: a smaller topological charge, a smaller initial radius, and an optimized half-ring width can alleviate degrading effects of turbulence on the pv beam. Additionally, the pv beam with a longer wavelength is more resistant to turbulent interference. The oceanic conditions with a higher dissipation rate of kinetic energy per unit mass of seawater, larger values of anisotropy and inner-scale factor, a smaller temperature-salinity contribution ratio, or a lower mean-squared temperature dissipation rate can improve the signal mode detection probability. The results are expected to further optimize the design of OAM-based underwater wireless communication systems.

Fluorescence imaging and Raman spectroscopy applied for the accurate diagnosis of breast cancer with deep learning algorithms.

Deep learning is usually combined with a single detection technique in the field of disease diagnosis. This study focused on simultaneously combining deep learning with multiple detection technologies, fluorescence imaging and Raman spectroscopy, for breast cancer diagnosis. A number of fluorescence images and Raman spectra were collected from breast tissue sections of 14 patients. Pseudo-color enhancement algorithm and a convolutional neural network were applied to the fluorescence image processing, so that the discriminant accuracy of test sets, 88.61%, was obtained. Two different BP-neural networks were applied to the Raman spectra that mainly comprised collagen and lipid, so that the discriminant accuracy of 95.33% and 98.67% of test sets were gotten, respectively. Then the discriminant results of fluorescence images and Raman spectra were counted and arranged into a characteristic variable matrix to predict the breast tissue samples with partial least squares (PLS) algorithm. As a result, the predictions of all samples are correct, with minor error of predictive value. This study proves that deep learning algorithms can be applied into multiple diagnostic optics/spectroscopy techniques simultaneously to improve the accuracy in disease diagnosis.