Defect-Free Arbitrary-Geometry Assembly of Mixed-Species Atom Arrays.

Optically trapped mixed-species single atom arrays with arbitrary geometry are an attractive and promising platform for various applications, because tunable quantum systems with multiple components provide extra degrees of freedom for experimental control. Here, we report the first demonstration of two-dimensional 6×4 dual-species atom assembly of ^{85}Rb (^{87}Rb) atoms with a filling fraction of 0.88 (0.89). This mixed-species atomic synthesis is achieved via rearranging initially randomly distributed atoms by a sorting algorithm (heuristic heteronuclear algorithm) which is designed for bottom-up atom assembly with both user-defined geometries and two-species atom number ratios. Our fully tunable hybrid-atom systems with scalable advantages are a good starting point for high-fidelity quantum logic, many-body quantum simulation, and single molecule array formation.

Values of OAS gene family in the expression signature, immune cell infiltration and prognosis of human bladder cancer.

BACKGROUND: Bladder cancer (BLCA) is one of the most common genitourinary malignancies in the world, but its pathogenic genes have not been fully identified and the treatment outcomes are still unsatisfactory. Although the members of 2', 5'-oligoadenylate synthetase (OAS) gene family are known involved in some tumorous biological processes, the roles of the OAS gene family in BLCA are still undetermined. METHODS: By combining vast bioinformatic datasets analyses of BLCA and the experimental verification on clinical BLCA specimen, we identified the expressions and biological functions of OAS gene family members in BLCA with comparison to normal bladder tissues. RESULTS: The expression levels of OAS gene family members were higher in BLCA than in normal bladder tissues. The expression levels of most OAS genes had correlations with genomic mutation and methylation, and with the infiltration levels of CD4 + T cells, CD8 + T cells, neutrophils, and dendritic cells in the microenvironment of BLCA. In addition, high expressions of OAS1, OAS2, OAS3, and OASL predicted better overall survival in BLCA patients. CONCLUSIONS: The highly expressed OAS genes in BLCA can reflect immune cells infiltration in the tumor microenvironment and predict the better overall survival of BLCA, and thus may be considered as a signature of BLCA. The study provides new insights into the diagnosis, treatment, and prognosis of BLCA.

Lens regeneration using endogenous stem cells with gain of visual function.

The repair and regeneration of tissues using endogenous stem cells represents an ultimate goal in regenerative medicine. To our knowledge, human lens regeneration has not yet been demonstrated. Currently, the only treatment for cataracts, the leading cause of blindness worldwide, is to extract the cataractous lens and implant an artificial intraocular lens. However, this procedure poses notable risks of complications. Here we isolate lens epithelial stem/progenitor cells (LECs) in mammals and show that Pax6 and Bmi1 are required for LEC renewal. We design a surgical method of cataract removal that preserves endogenous LECs and achieves functional lens regeneration in rabbits and macaques, as well as in human infants with cataracts. Our method differs conceptually from current practice, as it preserves endogenous LECs and their natural environment maximally, and regenerates lenses with visual function. Our approach demonstrates a novel treatment strategy for cataracts and provides a new paradigm for tissue regeneration using endogenous stem cells.

Upregulation of α enolase (ENO1) crotonylation in colorectal cancer and its promoting effect on cancer cell metastasis.

Lysine crotonylation (Kcr) is a newly identified protein translational modification and is involved in major biological processes including glycolysis, but its role in colorectal cancer (CRC) is unknown. Here, we found that the Kcr of α enolase (ENO1) was significantly elevated in human CRC tissues compared with the paratumoral tissues. CREB-binding protein (CBP) functioned as a crotonyltranferase of ENO1, and SIRT2 was involved in the decrotonylation of ENO1. Using quantitative mass spectrometry for crotonylomics analysis, we further found that K420 was the main Kcr site of ENO1 and ENO1 K420 Kcr promoted the growth, migration, and invasion of CRC cells in vitro by enhancing the activity of ENO1 and regulating the expression of tumor-associated genes. Our study reveals an important mechanism by which ENO1 regulates CRC through crotonylation.

DNA methylation markers for diagnosis and prognosis of common cancers.

The ability to identify a specific cancer using minimally invasive biopsy holds great promise for improving the diagnosis, treatment selection, and prediction of prognosis in cancer. Using whole-genome methylation data from The Cancer Genome Atlas (TCGA) and machine learning methods, we evaluated the utility of DNA methylation for differentiating tumor tissue and normal tissue for four common cancers (breast, colon, liver, and lung). We identified cancer markers in a training cohort of 1,619 tumor samples and 173 matched adjacent normal tissue samples. We replicated our findings in a separate TCGA cohort of 791 tumor samples and 93 matched adjacent normal tissue samples, as well as an independent Chinese cohort of 394 tumor samples and 324 matched adjacent normal tissue samples. The DNA methylation analysis could predict cancer versus normal tissue with more than 95% accuracy in these three cohorts, demonstrating accuracy comparable to typical diagnostic methods. This analysis also correctly identified 29 of 30 colorectal cancer metastases to the liver and 32 of 34 colorectal cancer metastases to the lung. We also found that methylation patterns can predict prognosis and survival. We correlated differential methylation of CpG sites predictive of cancer with expression of associated genes known to be important in cancer biology, showing decreased expression with increased methylation, as expected. We verified gene expression profiles in a mouse model of hepatocellular carcinoma. Taken together, these findings demonstrate the utility of methylation biomarkers for the molecular characterization of cancer, with implications for diagnosis and prognosis.

The Impact of Surgeons on the Likelihood of Mastectomy in Breast Cancer.

OBJECTIVE: This study evaluates the impact of individual surgeons and institutions on the use of mastectomy or breast conserving surgery (BCS) among elderly women with breast cancer. SUMMARY OF BACKGROUND DATA: Current literature characterizes patient clinical and demographic factors that increase likelihood of mastectomy use. However, the impact of the individual provider or institution is not well understood, and could provide key insights to biases in the decision-making process. METHODS: A retrospective cohort study of 29,358 women 65 years or older derived from the SEER-Medicare linked database with localized breast cancer diagnosed from 2000 to 2009. Multilevel, multivariable logistic models were employed, with odds ratios (ORs) used to describe the impact of demographic or clinical covariates, and the median OR (MOR) used to describe the relative impact of the surgeon and institution. RESULTS: Six thousand five hundred ninety-four women (22.4%) underwent mastectomy. Unadjusted rates of mastectomy ranged from 0% in the bottom quintile of surgeons to 58.0% in the top quintile. On multivariable analysis, the individual surgeon (MOR 1.97) had a greater impact on mastectomy than did the institution (MOR 1.71) or all other clinical and demographic variables except tumor size (OR 3.06) and nodal status (OR 2.95). Surgeons with more years in practice, or those with a lower case volume were more likely to perform mastectomy (P < 0.05). CONCLUSION: The individual surgeon influences the likelihood of mastectomy for the treatment of localized breast cancer. Further research should focus on physician-related biases that influence this decision to ensure patient autonomy.

Human milk oligosaccharide composition predicts risk of necrotising enterocolitis in preterm infants.

OBJECTIVE: Necrotising enterocolitis (NEC) is one of the most common and often fatal intestinal disorders in preterm infants. Markers to identify at-risk infants as well as therapies to prevent and treat NEC are limited and urgently needed. NEC incidence is significantly lower in breast-fed compared with formula-fed infants. Infant formula lacks human milk oligosaccharides (HMO), such as disialyllacto-N-tetraose (DSLNT), which prevents NEC in neonatal rats. However, it is unknown if DSLNT also protects human preterm infants. DESIGN: We conducted a multicentre clinical cohort study and recruited 200 mothers and their very low birthweight infants that were predominantly human milk-fed. We analysed HMO composition in breast milk fed to infants over the first 28 days post partum, matched each NEC case with five controls and used logistic regression and generalised estimating equation to test the hypothesis that infants who develop NEC receive milk with less DSLNT than infants who do not develop NEC. RESULTS: Eight infants in the cohort developed NEC (Bell stage 2 or 3). DSLNT concentrations were significantly lower in almost all milk samples in NEC cases compared with controls, and its abundance could identify NEC cases prior to onset. Aggregate assessment of DSLNT over multiple days enhanced the separation of NEC cases and control subjects. CONCLUSIONS: DSLNT content in breast milk is a potential non-invasive marker to identify infants at risk of developing NEC, and screen high-risk donor milk. In addition, DSLNT could serve as a natural template to develop novel therapeutics against this devastating disorder.

In Children With Nonalcoholic Fatty Liver Disease, Zone 1 Steatosis Is Associated With Advanced Fibrosis.

BACKGROUND & AIMS: Focal zone 1 steatosis, although rare in adults with nonalcoholic fatty liver disease (NAFLD), does occur in children with NAFLD. We investigated whether focal zone 1 steatosis and focal zone 3 steatosis are distinct subphenotypes of pediatric NAFLD. We aimed to determine associations between the zonality of steatosis and demographic, clinical, and histologic features in children with NAFLD. METHODS: We performed a cross-sectional study of baseline data from 813 children (age <18 years; mean age, 12.8 ± 2.7 years). The subjects had biopsy-proven NAFLD and were enrolled in the Nonalcoholic Steatohepatitis Clinical Research Network. Liver histology was reviewed using the Nonalcoholic Steatohepatitis Clinical Research Network scoring system. RESULTS: Zone 1 steatosis was present in 18% of children with NAFLD (n = 146) and zone 3 steatosis was present in 32% (n = 244). Children with zone 1 steatosis were significantly younger (10 vs 14 years; P < .001) and a significantly higher proportion had any fibrosis (81% vs 51%; P < .001) or advanced fibrosis (13% vs 5%; P < .001) compared with children with zone 3 steatosis. In contrast, children with zone 3 steatosis were significantly more likely to have steatohepatitis (30% vs 6% in children with zone 1 steatosis; P < .001). CONCLUSIONS: Children with zone 1 or zone 3 distribution of steatosis have an important subphenotype of pediatric NAFLD. Children with zone 1 steatosis are more likely to have advanced fibrosis and children with zone 3 steatosis are more likely to have steatohepatitis. To achieve a comprehensive understanding of pediatric NAFLD, studies of pathophysiology, natural history, and response to treatment should account for the zonality of steatosis.

Distinct splicing signatures affect converged pathways in myelodysplastic syndrome patients carrying mutations in different splicing regulators.

Myelodysplastic syndromes (MDS) are heterogeneous myeloid disorders with prevalent mutations in several splicing factors, but the splicing programs linked to specific mutations or MDS in general remain to be systematically defined. We applied RASL-seq, a sensitive and cost-effective platform, to interrogate 5502 annotated splicing events in 169 samples from MDS patients or healthy individuals. We found that splicing signatures associated with normal hematopoietic lineages are largely related to cell signaling and differentiation programs, whereas MDS-linked signatures are primarily involved in cell cycle control and DNA damage responses. Despite the shared roles of affected splicing factors in the 3' splice site definition, mutations in U2AF1, SRSF2, and SF3B1 affect divergent splicing programs, and interestingly, the affected genes fall into converging cancer-related pathways. A risk score derived from 11 splicing events appears to be independently associated with an MDS prognosis and AML transformation, suggesting potential clinical relevance of altered splicing patterns in MDS.

Circulating tumour DNA methylation markers for diagnosis and prognosis of hepatocellular carcinoma.

An effective blood-based method for the diagnosis and prognosis of hepatocellular carcinoma (HCC) has not yet been developed. Circulating tumour DNA (ctDNA) carrying cancer-specific genetic and epigenetic aberrations may enable a noninvasive 'liquid biopsy' for diagnosis and monitoring of cancer. Here, we identified an HCC-specific methylation marker panel by comparing HCC tissue and normal blood leukocytes and showed that methylation profiles of HCC tumour DNA and matched plasma ctDNA are highly correlated. Using cfDNA samples from a large cohort of 1,098 HCC patients and 835 normal controls, we constructed a diagnostic prediction model that showed high diagnostic specificity and sensitivity (P < 0.001) and was highly correlated with tumour burden, treatment response, and stage. Additionally, we constructed a prognostic prediction model that effectively predicted prognosis and survival (P < 0.001). Together, these findings demonstrate in a large clinical cohort the utility of ctDNA methylation markers in the diagnosis, surveillance, and prognosis of HCC.

High-dimensional variable selection and prediction under competing risks with application to SEER-Medicare linked data.

Competing risk analysis considers event times due to multiple causes or of more than one event types. Commonly used regression models for such data include (1) cause-specific hazards model, which focuses on modeling one type of event while acknowledging other event types simultaneously, and (2) subdistribution hazards model, which links the covariate effects directly to the cumulative incidence function. Their use in the presence of high-dimensional predictors are largely unexplored. Motivated by an analysis using the linked SEER-Medicare database for the purposes of predicting cancer versus noncancer mortality for patients with prostate cancer, we study the accuracy of prediction and variable selection of existing machine learning methods under both models using extensive simulation experiments, including different approaches to choosing penalty parameters in each method. We then apply the optimal approaches to the analysis of the SEER-Medicare data.

Analytical performance of three diagnostic reagents for HBsAg on an automatic ELISA analyzer.

PURPOSE: We conducted performance tests of three HBsAg ELISA diagnostic reagents using an Addcare 600 (Yantai Addcare Bio-tech Limited Company) and studied the consistency between the qualitative results and chemiluminescent microparticle immunoassay (CMIA) results. METHODS: Diagnostic kits (ELISA) for HBsAg manufactured by INTEC ("A"), KHB ("B") and Wantai ("C") were tested on an Addcare 600 to evaluate their intermediate precision, repeatability, and C50. Furthermore, three ELISA detection systems and a quantitative test kit for HBsAg (Abbott) were employed to screen 1000 serum samples, while CMIA reactive samples were used to perform the confirmatory tests. The evaluation indexes of the ELISA reagent performances were calculated. RESULTS: The intermediate precision and repeatability of each system were <14% and <9%, respectively, while C50 was 0.105-0.115 IU/mL. The sensitivities of A, B, and C were 98.70%, 99.28%, and 99.13%, respectively, while their specificities were 98.06%, 99.03%, and 97.42%, respectively. The Youden indexes were 96.76%, 98.31%, and 96.55%, respectively, while the kappa values were 0.965 (P=.000), 0.981 (P=.000), and 0.967 (P=.000), respectively. CONCLUSION: The combination of Addcare 600 with the three reagents could meet the clinical requirement. Reagent B demonstrated the best performance. Although the results consistency among the three systems and CMIA was good, our findings suggest that ELISA should be combined with a confirmatory test to exclude false-positive and false-negative results caused by low HBsAg levels.

Regularization method for predicting an ordinal response using longitudinal high-dimensional genomic data.

Abstract An ordinal scale is commonly used to measure health status and disease related outcomes in hospital settings as well as in translational medical research. In addition, repeated measurements are common in clinical practice for tracking and monitoring the progression of complex diseases. Classical methodology based on statistical inference, in particular, ordinal modeling has contributed to the analysis of data in which the response categories are ordered and the number of covariates (p) remains smaller than the sample size (n). With the emergence of genomic technologies being increasingly applied for more accurate diagnosis and prognosis, high-dimensional data where the number of covariates (p) is much larger than the number of samples (n), are generated. To meet the emerging needs, we introduce our proposed model which is a two-stage algorithm: Extend the generalized monotone incremental forward stagewise (GMIFS) method to the cumulative logit ordinal model; and combine the GMIFS procedure with the classical mixed-effects model for classifying disease status in disease progression along with time. We demonstrate the efficiency and accuracy of the proposed models in classification using a time-course microarray dataset collected from the Inflammation and the Host Response to Injury study.

Kinetic isotope effect of the (16)O + (36)O2 and (18)O + (32)O2 isotope exchange reactions: Dominant role of reactive resonances revealed by an accurate time-dependent quantum wavepacket study.

The O + O2 isotope exchange reactions play an important role in determining the oxygen isotopic composition of a number of trace gases in the atmosphere, and their temperature dependence and kinetic isotope effects (KIEs) provide important constraints on our understanding of the origin and mechanism of these and other unusual oxygen KIEs important in the atmosphere. This work reports a quantum dynamics study of the title reactions on the newly constructed Dawes-Lolur-Li-Jiang-Guo (DLLJG) potential energy surface (PES). The thermal reaction rate coefficients of both the (18)O + (32)O2 and (16)O + (36)O2 reactions obtained using the DLLJG PES exhibit a clear negative temperature dependence, in sharp contrast with the positive temperature dependence obtained using the earlier modified Siebert-Schinke-Bittererova (mSSB) PES. In addition, the calculated KIE shows an improved agreement with the experiment. These results strongly support the absence of the "reef" structure in the entrance/exit channels of the DLLJG PES, which is present in the mSSB PES. The quantum dynamics results on both PESs attribute the marked KIE to strong near-threshold reactive resonances, presumably stemming from the mass differences and/or zero point energy difference between the diatomic reactant and product. The accurate characterization of the reactivity for these near-thermoneutral reactions immediately above the reaction threshold is important for correct characterization of the thermal reaction rate coefficients.

Machine-learning intervention progress in the field of organic waste composting: Simulation, prediction, optimization, and challenges.

Aerobic composting stands as a widely-adopted method for treating organic solid waste (OSW), simultaneously producing organic fertilizers and soil amendments. This biologically-driven biochemical reaction process, however, presents challenges due to its complex non-linear metabolism and the heterogeneous nature of the solid medium. These characteristics inherently limit the simulation accuracy and efficiency optimization in aerobic composting. Recently, significant efforts have been made to simulate and control composting process parameters, as well as predicting and optimizing composting product quality. Notably, the integration of machine learning (ML) in aerobic composting of organic waste has garnered considerable attention for its applicability and predictive capability in exploring the complex non-linear relationships of organic waste composting parameters. Despite numerous studies on ML applications in OSW composting, a systematic review of research findings in this field is lacking. This study offers a systematic overview of the application level, current status, and versatility of ML in OSW composting. It spans various aspects, such as compost maturity, environmental pollutants, nutrients, moisture, heat loss, and microbial metabolism. The survey reveals that ML-intervention predominantly focuses on compost maturity and environmental pollutants, followed by nutrients, moisture, heat loss, and microbial activity. The most commonly employed predictive models and optimization algorithms are artificial neural networks (47%) and genetic algorithms (10%). These demonstrate high prediction accuracy and maximize composting efficiency in the simulation and prediction of organic waste composting, alongside regulation of key parameters. Deep neural networks and ensemble learning models prove effective in achieving superior predictive performance by selecting feature variables in compost maturity and pollutant residue prediction of organic waste composting in a simpler and more objective manner.

Novel perspective on qualitative assessment of swine manure compost maturity using organic carbon density fractions.

Mature compost is safe and stable, yet quality assessments are challenging owing to current maturity indicators' limitations. This study employed density fractionation to separate organic carbon into light and heavy fractions, offering a new perspective for assessing maturity. Results showed that light fraction organic carbon progressively transitioned into heavy fraction during composting, reducing the proportion of total organic carbon from 82.82% to 44.03%, while heavy fraction organic carbon increased to 48.58%. During the first seven days, the reduction rate of light fraction organic carbon decreased slowly, while the increase rate of heavy fraction declined sharply, levelling off thereafter. Light/heavy fraction organic carbon ratio was significantly correlated with existing maturity indicators (carbon/nitrogen ratio, humic acid/fulvic acid ratio, biological growth-related indicators), with the ratio below 1.33 serving as a potential compost maturity marker. Thus, given its simplicity and reliability, organic carbon density fractions is an innovative indicator for compost maturity assessments.

Effect of sanxan as novel natural gel modifier on the physicochemical and structural properties of microbial transglutaminase-induced mung bean protein isolate gels.

Mung bean protein isolate (MBPI) has attracted much attention as an emerging plant protein. However, its application was limited by the poor gelling characteristics. Thus, the effect of sanxan (SAN) on the gelling behavior of MBPI under microbial transglutaminase (MTG)-induced condition were explored in this study. The results demonstrated that SAN remarkably enhanced the storage modulus, water-holding capacity and mechanical strength. Furthermore, SAN changed the microstructure of MBPI gels to become more dense and ordered. The results of zeta potential indicated the electrostatic interactions existed between SAN and MBPI. The incorporation of SAN altered the secondary structure and molecular conformation of MBPI, and hydrophobic interactions and hydrogen bonding were necessary to maintain the network structure. Additionally, in vitro digestion simulation results exhibited that SAN remarkably improved the capability of MBPI gels to deliver bioactive substances. These findings provided a practical strategy to use natural SAN to improve legume protein gels.

Lactoferrin-Chitosan Composite Hydrogels Induced by Microbial Transglutaminase: Potential Delivery Systems for Thermosensitive Bioactive Substances.

In this work, lactoferrin (LF)-chitosan (CS) composite hydrogels with good loading capacity of thermosensitive bioactive substances were successfully obtained by microbial transglutaminase (MTG)-induced cross-linking. We evaluated the rheological, textural, and microstructural characteristics of the composite hydrogels under different conditions. The results demonstrated that the concentrations of LF and CS as well as the amount of MTG could regulate the textural properties, rheological properties, and water holding capability. The results of FTIR and fluorescence spectroscopy indicated that the main interactions within the composite gel were hydrogen and isopeptide bonds. Additionally, in vitro digestion simulation results verified that riboflavin kept stable in stomach due to the protection of LF-CS composite hydrogels and was released in small intestine. These results suggested that thermosensitive bioactive substance could be encapsulated and delivered by the LF-CS composite hydrogel, which could be applied in lots of potential applications in functional food as a new material.

Mechanism on microbial transglutaminase and Tremella fuciformis polysaccharide-mediated modification of lactoferrin: Development of functional food.

Lactoferrin (LF) with various biological functions demonstrates great application potential. However, its application was restricted by its poor gelation and instability. The aim of this work was to explore the effect of microbial transglutaminase (MTGase) and Tremella fuciformis polysaccharide (TP) on the functional properties of LF. The formation of a self-supporting LF gel could be induced by MTGase through generating covalent crosslinks between the LF protein molecules. Meanwhile, TP was introduced into the gel system to improve the strength of LF-TP composite gels by enhancing non-covalent interactions such as hydrogen bond and electrostatic interactions during gel formation. Additionally, the LF-TP composite gel exhibited outstanding functional characteristics such as gastrointestinal digestive stability and antioxidant property. This work clarified the mechanism on MTGase and TP-mediated modification of lactoferrin, offered a novel strategy to increase the functional characteristics of LF, and enlarged the application range of LF and TP.