Microfluidic Electrochemical Integrated Sensor for Efficient and Sensitive Detection of Candida albicans.

Traditional methods for the detection of pathogenic bacteria are time-consuming, less efficient, and sensitive, which affects infection control and bungles illness. Therefore, developing a method to remedy these problems is very important in the clinic to diagnose the pathogenic diseases and guide the rational use of antibiotics. Here, microfluidic electrochemical integrated sensor (MEIS) has been investigated, functionally for rapid, efficient separation and sensitive detection of pathogenic bacteria. Three-dimensional macroporous PDMS and Au nanotube-based electrode are successfully assembled into the modeling microchip, playing the functions of "3D chaotic flow separator" and "electrochemical detector," respectively. The 3D chaotic flow separator enhances the turbulence of the fluid, achieving an excellent bacteria capture efficiency. Meanwhile, the electrochemical detector provides a quantitative signal through enzyme-linked immunoelectrochemistry with improved sensitivity. The microfluidic electrochemical integrated sensor could successfully isolate Candida albicans (C. albicans) in the range of 30-3,000,000 CFU in the saliva matrix with over 95% capture efficiency and sensitively detect C. albicans in 1 h in oral saliva samples. The integrated device demonstrates great potential in the diagnosis of oral candidiasis and is also applicable in the detection of other pathogenic bacteria.

Similarity measures-based graph co-contrastive learning for drug-disease association prediction.

MOTIVATION: An imperative step in drug discovery is the prediction of drug-disease associations (DDAs), which tries to uncover potential therapeutic possibilities for already validated drugs. It is costly and time-consuming to predict DDAs using wet experiments. Graph Neural Networks as an emerging technique have shown superior capacity of dealing with DDA prediction. However, existing Graph Neural Networks-based DDA prediction methods suffer from sparse supervised signals. As graph contrastive learning has shined in mitigating sparse supervised signals, we seek to leverage graph contrastive learning to enhance the prediction of DDAs. Unfortunately, most conventional graph contrastive learning-based models corrupt the raw data graph to augment data, which are unsuitable for DDA prediction. Meanwhile, these methods could not model the interactions between nodes effectively, thereby reducing the accuracy of association predictions. RESULTS: A model is proposed to tap potential drug candidates for diseases, which is called Similarity Measures-based Graph Co-contrastive Learning (SMGCL). For learning embeddings from complicated network topologies, SMGCL includes three essential processes: (i) constructs three views based on similarities between drugs and diseases and DDA information; (ii) two graph encoders are performed over the three views, so as to model both local and global topologies simultaneously; and (iii) a graph co-contrastive learning method is introduced, which co-trains the representations of nodes to maximize the agreement between them, thus generating high-quality prediction results. Contrastive learning serves as an auxiliary task for improving DDA predictions. Evaluated by cross-validations, SMGCL achieves pleasing comprehensive performances. Further proof of the SMGCL's practicality is provided by case study of Alzheimer's disease. AVAILABILITY AND IMPLEMENTATION: https://github.com/Jcmorz/SMGCL.

PmAGAMOUS recruits polycomb protein PmLHP1 to regulate single-pistil morphogenesis in Japanese apricot.

Japanese apricot (Prunus mume Sieb. et Zucc.) is a traditional fruit tree with a long history. Multiple pistils (MP) lead to the formation of multiple fruits, decreasing fruit quality and yield. In this study, the morphology of flowers was observed at 4 stages of pistil development: undifferentiated stage (S1), predifferentiation stage (S2), differentiation stage (S3), and late differentiation stage (S4). In S2 and S3, the expression of PmWUSCHEL (PmWUS) in the MP cultivar was significantly higher than that in the single-pistil (SP) cultivar, and the gene expression of its inhibitor, PmAGAMOUS (PmAG), also showed the same trend, indicating that other regulators participate in the regulation of PmWUS during this period. Chromatin immunoprecipitation-qPCR (ChIP-qPCR) showed that PmAG could bind to the promoter and the locus of PmWUS, and H3K27me3 repressive marks were also detected at these sites. The SP cultivar exhibited an elevated level of DNA methylation in the promoter region of PmWUS, which partially overlapped with the region of histone methylation. This suggests that the regulation of PmWUS involves both transcription factors and epigenetic modifications. Also, the gene expression of Japanese apricot LIKE HETEROCHROMATIN PROTEIN (PmLHP1), an epigenetic regulator, in MP was significantly lower than that in SP in S2 to 3, contrary to the trend in expression of PmWUS. Our results showed that PmAG recruited sufficient PmLHP1 to maintain the level of H3K27me3 on PmWUS during the S2 of pistil development. This recruitment of PmLHP1 by PmAG inhibits the expression of PmWUS at the precise time, leading to the formation of 1 normal pistil primordium.

Hybrid Local and Charge-Transfer Material with Ultralong Room Temperature Phosphorescence for Efficient Organic Afterglow Light-Emitting Diodes.

Organic ultralong room temperature phosphorescence (OURTP) materials capable of combining various emission behaviors for diversified optoelectronic properties and applications have recently gained a vigorous development, but it remains a forbidden challenge in designing OURTP molecules with hybrid local and charge-transfer (HLCT) feature, possibly due to the elevated difficulties in simultaneously meeting the stringent requirements of both HLCT and OURTP emitters. Here, through introducing multiple heteroatoms into one-dimensional fused ring of coumarin with moderate charge transfer perturbation in donor-π-acceptor architecture, we demonstrate a HLCT-featured OURTP molecule showing both promoted fluorescence with a quantum yield of 77% in solution and long-lived OURTP with a lifetime of 251 ms in conventional host material used in electroluminescent device. Thus, efficient OURTP organic light-emitting diodes (OLEDs) were fabricated, exhibiting bright electroluminescence with an exciton utilization efficiency of 85% and yellow OURTP lasting over 2 s for afterglow. Impressively, the HLCT OURTP-OLEDs can be further optimized to reach an unprecedented total external quantum efficiency (EQE) of ~12% and OURTP EQE up to 3.11%, representing the highest performance among the reported OURTP-OLEDs. These impressive results highlight the significance to fuse HLCT and OURTP together in enriching OURTP materials and improving the afterglow OLED performances.

A single-centre, open-label, single-arm, fixed-sequence pharmacokinetic study of SHR3680 on repaglinide and bupropion in prostate cancer patients.

To evaluate the pharmacokinetic effects of SHR3680 on repaglinide and bupropion and its metabolite hydroxybupropion. METHODS: A single-centre, open-label, single-arm, fixed-sequence clinical trial in 18 patients with prostate cancer. RESULTS: After a single oral dose of 0.5 mg repaglinide and SHR3680, geometric mean peak plasma concentration (Cmax ) of plasma repaglinide was 14.240 and 5.887 ng/mL, geometric mean area under the concentration-time curve (AUC0-t )was 20.577 and 7.320 h ng/mL, geometric mean AUC0-∞ was 20.949 and 7.451 h ng/mL, mean half-life (t1/2 ) was 1.629 and 1.195 hours, and geometric mean oral clearance (CL/F) was 23.867 and 67.107 L/h, respectively. After a single oral administration of 150 mg bupropion and SHR3680, geometric mean Cmax of plasma bupropion was 85.430 and 33.747 ng/mL, geometric mean AUC0-t was 1003.896 and 380.158 h ng/mL, geometric mean AUC0-∞ was 1038.054 and 401.387 h ng/mL, mean t1/2 was 22.533 and 17.733 hours, and geometric mean CL/F was 144.501 and 373.705 L/h, respectively. The plasma geometric mean Cmax of its main active metabolic hydroxybupropion was 268.113 and 177.318 ng/mL, geometric mean AUC0-t was 14 283.087 and 5420.219 h ng/mL, geometric mean AUC0-∞ was 15 218.158 and 5364.625 h ng/mL, mean t1/2 were 36.069 and 16.688 hours, and geometric mean CL/F was 8.623 L/h and 27.961 L/h, respectively. CONCLUSION: Coadministration of SHR3680 with repaglinide or bupropion significantly shortened the elimination half-lives, significantly increased the apparent clearance rate, and significantly decreased the in vivo exposure of repaglinide, bupropion and hydroxybupropion compared with single administration of repaglinide or bupropion.

Impact of the COVID-19 pandemic and the dynamic COVID-zero strategy on HIV incidence and mortality in China.

BACKGROUND: In response to the coronavirus disease 2019 (COVID-19) pandemic, the Chinese government implemented the dynamic COVID-zero strategy. We hypothesized that pandemic mitigation measures might have reduced the incidence, mortality rates, and case fatality ratios (CFRs) of the human immunodeficiency virus (HIV) in 2020-2022. METHOD: We collected HIV incidence and mortality data from the website of the National Health Commission of the People's Republic of China from January 2015 to December 2022. We compared the observed and predicted HIV values in 2020-2022 with those in 2015-2019 using a two-ratio Z-test. RESULTS: From January 1, 2015, to December 31, 2022, a total of 480,747 HIV incident cases were reported in mainland China, of which 60,906 (per year) and 58,739 (per year) were reported in 2015-2019 (pre-COVID-19 stage) and 2020-2022 (post-COVID-19 stage), respectively. The average yearly HIV incidence decreased by 5.2450% (from 4.4143 to 4.1827 per 100,000 people, p <  0.001) in 2020-2022 compared with that in 2015-2019. However, the average yearly HIV mortality rates and CFRs increased by 14.1076 and 20.4238%, respectively (all p <  0.001), in 2020-2022 compared with those in 2015-2019. During the emergency phase in January 2020 to April 2020, the monthly incidence was significantly lower (23.7158%) than that during the corresponding period in 2015-2019, while the incidence during the routine stage in May 2020-December 2022 increased by 27.4334%, (all p <  0.001). The observed incidence and mortality rates for HIV decreased by 16.55 and 18.1052% in 2020, by 25.1274 and 20.2136% in 2021, and by 39.7921 and 31.7535% in 2022, respectively, compared with the predicted values, (all p <  0.001). CONCLUSIONS: The findings suggest that China's dynamic COVID-zero strategy may have partly disrupted HIV transmission and further slowed down its growth. Without China's dynamic COVID-zero strategy, HIV incidence and deaths in the country would have likely remained high in 2020-2022. There is an urgent need to expand and improve HIV prevention, care, and treatment, as well as surveillance in the future.

Analysis of Risk Factors for Complications after Percutaneous Coronary Intervention in Patients with Acute ST-segment Elevation Myocardial Infarction.

Background: Acute ST segment elevation myocardial infarction (ASTEMI) is the most common and serious type of AMI, percutaneous coronary intervention (PCI) is currently the most commonly used approach for clinical treatment of ASTEMI. After PCI, patients with ASTEMI are very prone to various complications, which will seriously threaten their health and life safety. Objective: This study aims to analyze the risk factors for complications in patients with acute ST-segment elevation myocardial infarction (ASTEMI) treated with percutaneous coronary intervention (PCI). Methods: A total of 107 patients with ASTEMI who were subjected to PCI from October 2021 to December 2022 were selected as study subjects. Patients were divided into a safety group (no complications, n = 63) and a risk group (n = 45) based on the presence of postoperative complications. Baseline data (age, sex, etc.), Killip classification, left ventricular ejection fractions (LVEF), and routine blood test results were collected from patients in both groups for Logistic regression analysis to obtain relevant factors affecting the occurrence of post-PCI complications. Results: There were no differences between the safety group and the risk group in terms of sex, age, body mass index (BMI), Killip classification, and infarct site (P > .05). Compared with the safety group, the risk group exhibited a higher proportion of patients with multiple pre-existing diseases, LVEF < 40%, and number of coronary artery lesions ≥ 1, and higher levels of hs-CRP, NT-proBNP, HbA1c and Scr (P < .05). Logistic regression analysis results showed that multiple pre-existing diseases, hs-CRP, NT-proBNP, HbA1c, and Scr were relevant factors affecting the occurrence of post-PCI complications (P < .05). Conclusion: Multiple pre-existing diseases, hs-CRP, NT-proBNP, HbA1c, and Scr were all independent risk factors for the occurrence of post-PCI complications. Future clinical attention should be paid to these indicators in patients with ASTEMI in order to prevent post-PCI complications.

Handheld volumetric photoacoustic/ultrasound imaging using an internal scanning mechanism.

Photoacoustic/ultrasound (PA/US) dual-modality imaging has been evolving rapidly for the last two decades. Handheld PA/US probes with different implementations have attracted particular attention due to their convenience and high applicability. However, developing a volumetric dual-modality PA/US imaging probe with a compact design remains a challenge. Here, we develop a handheld volumetric PA/US imaging probe with a special light-ultrasound coupling design and an internal scanning mechanism. A coaxial design for the excitation and detection paths in a customized 3D-printed housing with a size of 110 × 90 × 64 mm3 is proposed to optimize the signal-to-noise ratio (SNR) of the handheld probe for deep tissue imaging. Two parallel and synchronously rotational acoustic reflectors allow for volumetric imaging with an effective field of view (FOV) of more than 30 mm × 20 mm × 8 mm. In addition to simulation and phantom validations, in vivo human trials are successfully carried out, demonstrating the high imaging quality and stability of the system for potential clinical translations.

Analysis of Influencing Factors of Unplanned Readmission in Patients With Acute Coronary Syndrome Within 30 Days After PCI.

OBJECTIVE: The purpose of this study is to identify the influencing factors of unplanned readmission in patients with the acute coronary syndrome (ACS) within 30 days after percutaneous coronary intervention (PCI). METHODS: From November 1, 2018, to October 31, 2019, the clinical data of 1277 patients with acute coronary syndrome and percutaneous coronary intervention retrospectively were collected. After screening by exclusion and rejection criteria, a total of 936 patients finally entered the study. Patients were divided into the readmission group (57 cases) and the non-readmission group (879 cases), according to whether unplanned readmission occurred within 30 days after PCI. To analyze the influence of patients' age, past disease history, medication history, laboratory data, vascular diseases, and other factors on readmission and the clinical characteristics of readmission patients. RESULTS: Fifty-seven patients had unplanned readmission within 30 days, and the readmission rate was 6.09%. The clinical features of readmission patients are older age, longer hospitalization days, more emergency percutaneous coronary intervention, more patients with diabetes history, and more patients diagnosed with ST-segment elevation myocardial infarction and non-ST-segment elevation myocardial infarction. Logistic regression analysis revealed that smoking index, number of diseased vessels, ACEF score, diabetes, and PCI status were the influencing factors of unplanned readmission of ACS patients within 30 days after PCI. CONCLUSION: Smoking index, number of diseased vessels, ACEF score, diabetes, and PCI status are the influencing factors of unplanned readmission within 30 days after percutaneous coronary intervention for patients with acute coronary syndrome.

FIRE: knowledge-enhanced recommendation with feature interaction and intent-aware attention networks.

To solve the information overload issue and enhance the user experience of various web applications, recommender systems aim to better model user interests and preferences. Knowledge Graphs (KGs), consisting of real-world objective facts and fruitful entities, play a vital role in recommender systems. Recently, a technological trend has been to develop end-to-end Graph Neural Networks (GNNs)-based knowledge-aware recommendation (a.k.a., Knowledge Graph Recommendation, KGR) models. Unfortunately, current GNNs-based KGR approaches focus on how to capture high-order feature information on KGs while neglecting the following two crucial limitations: 1) The explicitly high-order feature interaction and fusion mechanism and 2) The valid user intent modelling mechanism. As such, these issues lead to insufficient user/item representation learning capability and unsatisfactory KGR performance. In this work, we present a novel Knowledge-enhanced Re commendation with F eature I nteraction and Intent-aware Attention Networks (FIRE) to address the latent intent modelling and high-order feature interaction deficiencies ignored by existing KGR methods. Based on the prototype user/item representation learning leveraging the GNNs-based approach, our model offers the following major improvements: One is the innovative use of Convolutional Neural Networks (CNNs) that perform vertical convolutional (a.k.a., bit-level convolutional) and horizontal convolutional (a.k.a., vector-level convolutional) processes to model multi-granular high-order feature interactions to enhance item-side representation learning. Another is to model users' latent intent factors by utilizing a two-level attention mechanism (i.e., node- and intent-level attention mechanism) to enhance user-side representation learning. Extensive experiments on three KGs domain public datasets demonstrate that our method outperforms the existing state-of-the-art baseline. Last but not least, numerous ablation- and model studies demystify the working mechanism and elucidate the plausibility of the proposed model.

A Three-Dimensional Conductive Scaffold Microchip for Effective Capture and Recovery of Circulating Tumor Cells with High Purity.

Effective acquirement of highly pure circulating tumor cells (CTCs) is very important for CTC-related research. However, it is a great challenge since abundant white blood cells (WBCs) are always co-collected with CTCs because of nonspecific bonding or low depletion rate of WBCs in various CTC isolation platforms. Herein, we designed a three-dimensional (3D) conductive scaffold microchip for highly effective capture and electrochemical release of CTCs with high purity. The conductive 3D scaffold was prepared by dense immobilization of gold nanotubes (Au NTs) on porous polydimethylsiloxane and was functionalized with a CTC-specific biomolecule facilitated by a Au-S bond before embedding into a microfluidic device. The spatially distributed 3D macroporous structure compelled cells to change migration from linear to chaotic and the densely covered Au NTs enhanced the topographic interaction between cells and the substrate, thus synergistically improving the CTC capture efficiency. The Au NT-coated 3D scaffold had good electrical conductivity and the Au-S bond was breakable by voltage exposure so that captured CTCs could be specifically released by electrochemical stimulation while nonspecifically bonded WBCs were not responsive to this process, facilitating recovery of CTCs with high purity. The 3D conductive scaffold microchip was successfully applied to obtain highly pure CTCs from cancer patients' blood, benefiting the downstream analysis of CTCs.

Multi-modality photoacoustic/ultrasound imaging based on a commercial ultrasound platform.

Multimodal imaging takes advantage of each modality and has become a recent trend in the field of biomedical imaging. In this Letter, we develop and evaluate an integrated multi-modality imaging system combining photoacoustic computed tomography, optical resolution photoacoustic microscopy, brightness mode, and power Doppler ultrasound imaging on a commercial ultrasonographic platform. Using different imaging modalities enables the hybrid system to recover dense vascular networks and hemodynamic and morphological variations in both superficial and deep tissues. To evaluate the performance and illustrate the advantages of this system, we carried out both phantom and in vivo experiments. In addition to the complementary tissue information offered by different imaging modalities, the use of a commercial ultrasound platform shows the feasibility of the proposed method for future clinical translation.

Redirection of the central metabolism of Klebsiella pneumoniae towards dihydroxyacetone production.

BACKGROUND: Klebsiella pneumoniae is a bacterium that can be used as producer for numerous chemicals. Glycerol can be catabolised by K. pneumoniae and dihydroxyacetone is an intermediate of this catabolism pathway. Here dihydroxyacetone and glycerol were produced from glucose by this bacterium based a redirected glycerol catabolism pathway. RESULTS: tpiA, encoding triosephosphate isomerase, was knocked out to block the further catabolism of dihydroxyacetone phosphate in the glycolysis. After overexpression of a Corynebacterium glutamicum dihydroxyacetone phosphate dephosphorylase (hdpA), the engineered strain produced remarkable levels of dihydroxyacetone (7.0 g/L) and glycerol (2.5 g/L) from glucose. Further increase in product formation were obtained by knocking out gapA encoding an iosenzyme of glyceraldehyde 3-phosphate dehydrogenase. There are two dihydroxyacetone kinases in K. pneumoniae. They were both disrupted to prevent an inefficient reaction cycle between dihydroxyacetone phosphate and dihydroxyacetone, and the resulting strains had a distinct improvement in dihydroxyacetone and glycerol production. pH 6.0 and low air supplement were identified as the optimal conditions for dihydroxyacetone and glycerol production by K, pneumoniae ΔtpiA-ΔDHAK-hdpA. In fed batch fermentation 23.9 g/L of dihydroxyacetone and 10.8 g/L of glycerol were produced after 91 h of cultivation, with the total conversion ratio of 0.97 mol/mol glucose. CONCLUSIONS: This study provides a novel and highly efficient way of dihydroxyacetone and glycerol production from glucose.

Flexible Three-Dimensional Net for Intravascular Fishing of Circulating Tumor Cells.

Current strategies for in vitro isolation of circulating tumor cells (CTCs) fail to detect extremely rare CTCs heterogeneously distributed in blood. It is possible to devise methods for in vivo capture of CTCs based on processing almost all of the blood in the human body to improve detection sensitivity, but the complicated manipulation, biosafety concerns, and limited capture efficiency of conventional detection strategies prohibit their implementation in the clinic. Herein, we present a flexible three-dimensional (3-D) CTC-Net probe for intravascular collection of CTCs. The CTC-Net, consisting of a 3-D elastic scaffold with an interconnected, spatially distributed network accommodates a large quantity of immobilized antibodies and provides an enhanced substrate-cell contact frequency, which results in an enhanced capture efficiency and effective detection of heterogeneous CTCs. The as-prepared CTC-Net can be readily compressed and injected into blood vessels and fully unfolded to form a 3-D "fishing-net" structure for capture of the CTCs, and then retracted for imaging and downstream gene analysis of the captured CTCs. Significant advantages for the CTC-Net over currently available in vitro and in vivo procedures are demonstrated for detection of extremely rare CTCs from wild-type rats and successful capture of CTCs and CTC clusters before metastasis in the case of tumor-bearing rats. Our research demonstrates for the first time the use of a 3-D scaffold CTC-Net probe for in vivo capture of CTCs. The method shows exceptional performance for cell capture, which is readily implemented and holds great potential in the clinic for early diagnosis of cancer.

Ethylene glycol and glycolic acid production from xylonic acid by Enterobacter cloacae.

BACKGROUND: Biological routes for ethylene glycol production have been developed in recent years by constructing the synthesis pathways in different microorganisms. However, no microorganisms have been reported yet to produce ethylene glycol naturally. RESULTS: Xylonic acid utilizing microorganisms were screened from natural environments, and an Enterobacter cloacae strain was isolated. The major metabolites of this strain were ethylene glycol and glycolic acid. However, the metabolites were switched to 2,3-butanediol, acetoin or acetic acid when this strain was cultured with other carbon sources. The metabolic pathway of ethylene glycol synthesis from xylonic acid in this bacterium was identified. Xylonic acid was converted to 2-dehydro-3-deoxy-D-pentonate catalyzed by D-xylonic acid dehydratase. 2-Dehydro-3-deoxy-D-pentonate was converted to form pyruvate and glycolaldehyde, and this reaction was catalyzed by an aldolase. D-Xylonic acid dehydratase and 2-dehydro-3-deoxy-D-pentonate aldolase were encoded by yjhG and yjhH, respectively. The two genes are part of the same operon and are located adjacent on the chromosome. Besides yjhG and yjhH, this operon contains four other genes. However, individually inactivation of these four genes had no effect on either ethylene glycol or glycolic acid production; both formed from glycolaldehyde. YqhD exhibits ethylene glycol dehydrogenase activity in vitro. However, a low level of ethylene glycol was still synthesized by E. cloacae ΔyqhD. Fermentation parameters for ethylene glycol and glycolic acid production by the E. cloacae strain were optimized, and aerobic cultivation at neutral pH were found to be optimal. In fed batch culture, 34 g/L of ethylene glycol and 13 g/L of glycolic acid were produced in 46 h, with a total conversion ratio of 0.99 mol/mol xylonic acid. CONCLUSIONS: A novel route of xylose biorefinery via xylonic acid as an intermediate has been established.

2,3-Dihydroxyisovalerate production by Klebsiella pneumoniae.

2,3-Dihydroxyisovalerate is an intermediate of valine and leucine biosynthesis pathway; however, no natural microorganism has been found yet that can accumulate this compound. Klebsiella pneumoniae is a useful bacterium that can be used as a workhorse for the production of a range of industrially desirable chemicals. Dihydroxy acid dehydratase, encoded by the ilvD gene, catalyzes the reaction of 2-ketoisovalerate formation from 2,3-dihydroxyisovalerate. In this study, an ilvD disrupted strain was constructed which resulted in the inability to synthesize 2-ketoisovalerate, yet accumulate 2,3-dihydroxyisovalerate in its culture broth. 2,3-Butanediol is the main metabolite of K. pneumoniae and its synthesis pathway and the branched-chain amino acid synthesis pathway share the same step of the α-acetolactate synthesis. By knocking out the budA gene, carbon flow into the branched-chain amino acid synthesis pathway was upregulated, which resulted in a distinct increase in 2,3-dihydroxyisovalerate levels. Lactic acid was identified as a by-product of the process and by blocking the lactic acid synthesis pathway, a further increase in 2,3-dihydroxyisovalerate levels was obtained. The culture parameters of 2,3-dihydroxyisovalerate fermentation were optimized, which include acidic pH and medium level oxygen supplementation to favor 2,3-dihydroxyisovalerate synthesis. At optimal conditions (pH 6.5, 400 rpm), 36.5 g/L of 2,3-dihydroxyisovalerate was produced in fed-batch fermentation over 45 h, with a conversion ratio of 0.49 mol/mol glucose. Thus, a biological route of 2,3-dihydroxyisovalerate production with high conversion ratio and final titer was developed, providing a basis for an industrial process. Key Points • A biological route of 2,3-dihydroxyisovalerate production was setup. • Disruption of budA causes 2,3-dihydroxuisovalerate accumulation in K. pneumoniae. • Disruption of ilvD prevents 2,3-dihydroxyisovalerate reuse by the cell. • 36.5 g/L of 2,3-dihydroxyisovalerate was obtained in fed-batch fermentation.

Dietary fatty acids affect lipid metabolism and estrogen receptor expression in N-methyl-N-nitrosourea-induced rat mammary cancer model.

BACKGROUND: We hypothesized that dietary polyunsaturated fatty acids (PUFA) could affect the expression of serum fatty acid binding protein 5 (FABP5) and CD36 levels and also fatty acid synthase (FAS), and estrogen receptor (ER) expressions in breast cancer cells. METHODS: A rat mammary cancer model was induced by injection i.p., with 50 mg MNU/kg body weight. Low (13.8% energy) or high-fat (42.5% energy) diets composed mainly of n-6 or n-3 PUFAs originating either from linoleic acid or linolenic acid, respectively, were given for eight weeks. After sacrifice at week 8, serum FABP5 level was examined and immunostainings of CD36, FAS, and ER of breast cancer tissue were observed. RESULTS: By week 8, there was no statistical difference of tumor formation rate between each group. The level of serum FABP5 in the high n-3 group was significantly lower than the low n-6 and high n-6 groups. Immunohistochemistry results showed that there was a significant difference of CD36 expression between the low n-3 group and high n-6 group (p < 0.05). Although the high n-3 group had the most inhibition on FAS and ER expression, there was no statistical difference between each group. CONCLUSIONS: Our study showed that different dietary PUFAs may affect lipid metabolism in breast cancer tissues by altering the expression of FABP5, CD-36, FAS, and ER, which may change treatment response and even prognosis of breast cancer.

Effect of n-3 and n-6 polyunsaturated fatty acids on lipid metabolic genes and estrogen receptor expression in MCF-7 breast cancer cells.

BACKGROUND: To investigate the effect of different ratios of n-6/n-3 polyunsaturated fatty acids (PUFAs) on the expression of lipid metabolic genes and estrogen receptor (ER). METHODS: This study took place in the Department of Surgery, Women's Hospital, School of Medicine, Zhejiang University, Hangzhou, China, between January 2012 and October 2013. MCF-7 breast cancer cells were cultured for 48 hours with different ratios of PUFAs. Cell proliferation capability was detected by MTT method. Lipid metabolic genes and estrogen receptor (ER) were detected by western blot. RESULTS: Compared with the control group, the single n-6 PUFA group had no effect on sterol-regulatory-element-bindingprotein (SREBP) and fatty acid synthase (FAS) expression, while other groups all inhibited their expressions. Single n-6 group and 2:1 n-6/n-3 group down-regulated the expression of peroxisome proliferator-activated receptor (PPARγ), while in the other groups it was up-regulated. Single n-3 and n-6 groups had no effect on ER expression, while the others all suppressed the ER expression. CONCLUSIONS: Different ratios of n-6/n-3 polyunsaturated fatty acids may suppress the ER expression of MCF-7 cells and the effect may be related to its effect on the expression of lipid metabolic genes.

Accuracy of death risk prediction models for acute coronary syndrome patients: a systematic review and meta-analysis.

INTRODUCTION: This study systematically evaluates the accuracy of several death risk prediction models for patients with acute coronary syndrome (ACS) through evidence-based methods. We identify the most accurate and effective ACS death risk prediction model and provide an evidence-based basis for clinical healthcare personnel to evaluate their choice of death risk prediction model for ACS patients. EVIDENCE ACQUISITION: An evidence-based approach was used to study the current death risk prediction model for ACS. First, a literature search was carried out using computer-based and manual searching. The literature databases searched include Cochrane Library, MEDLINE, EMBASE, PubMed, Web of Science, WanFang Data, CNKI, VPCS, and SinoMed. The search period was limited to 2009 to 2022. Screening, quality evaluation and data extraction were carried out for the included articles. The PROBAST was used to conduct a migration risk assessment. RevMan 5.3 and Meta-DiSc 1.4 were used in combination to determine the model effect sizes. A descriptive analysis was conducted for the data that could not be meta-analyzed. EVIDENCE SYNTHESIS: A total of 8277 articles were initially included in this study. After screening, 25 articles were finally included, involving 11 different risk prediction models. A total of 306,390 patients with ACS were included of which 158,080 (51.6%) were male and 147,793 (48.4%) were female. The patients stemmed from 11 different countries (e.g., China, the USA, Spain, the UK, etc.). The total number of deaths was 23,601. The sensitivity of the GRACE risk prediction model was 0.78, with a specificity of 0.76 and an AUC value of 0.86. The sensitivity of the CAMI risk prediction model was 0.78, with a specificity of 0.70 and an AUC value of 0.85. The sensitivity of the TIMI risk prediction model was 0.51, with a specificity of 0.81, and an AUC value of 0.64. The sensitivity of the REMS risk prediction model was 0.78, with a specificity of 0.46 and an AUC value of 0.41. Eight different risk prediction models (EPICOR, CRUSADE, SAMI, GWTG, LNS, SYNTAX II, APACHE II) that could not be combined with the effect size were also included, with sensitivities ranging from 0.77-0.95, specificities ranging from 0.22-0.99, and AUC values ranging from 0.71-0.92. CONCLUSIONS: The GRACE and CAMI risk prediction models demonstrate good accuracy for evaluating the death risk of ACS patients. The accuracy of the TIMI risk prediction model is similar to that of the REMS risk prediction model. The APACHE II, SYNTAX II, EPICOR, and CAMI risk prediction models also show good accuracy for estimating the risk of death in ACS patients, although further validation is needed due to limited evidence. For improved predictive accuracy and to help advance medical interventions, the author recommends that clinical medical staff use the GRACE model to predict the death risk of ACS patients.

Vertebral HU value and the pectoral muscle index based on chest CT can be used to opportunistically screen for osteoporosis.

BACKGROUND: Existing studies have shown that computed tomography (CT) attenuation and skeletal muscle tissue are strongly associated with osteoporosis; however, few studies have examined whether vertebral HU values and the pectoral muscle index (PMI) measured at the level of the 4th thoracic vertebra (T4) are strongly associated with bone mineral density (BMD). In this study, we demonstrate that vertebral HU values and the PMI based on chest CT can be used to opportunistically screen for osteoporosis and reduce fracture risk through prompt treatment. METHODS: We retrospectively evaluated 1000 patients who underwent chest CT and DXA scans from August 2020-2022. The T4 HU value and PMI were obtained using manual chest CT measurements. The participants were classified into normal, osteopenia, and osteoporosis groups based on the results of dual-energy X-ray (DXA) absorptiometry. We compared the clinical baseline data, T4 HU value, and PMI between the three groups of patients and analyzed the correlation between the T4 HU value, PMI, and BMD to further evaluate the diagnostic efficacy of the T4 HU value and PMI for patients with low BMD and osteoporosis. RESULTS: The study ultimately enrolled 469 participants. The T4 HU value and PMI had a high screening capacity for both low BMD and osteoporosis. The combined diagnostic model-incorporating sex, age, BMI, T4 HU value, and PMI-demonstrated the best diagnostic efficacy, with areas under the receiver operating characteristic curve (AUC) of 0.887 and 0.892 for identifying low BMD and osteoporosis, respectively. CONCLUSIONS: The measurement of T4 HU value and PMI on chest CT can be used as an opportunistic screening tool for osteoporosis with excellent diagnostic efficacy. This approach allows the early prevention of osteoporotic fractures via the timely screening of individuals at high risk of osteoporosis without requiring additional radiation.