Improved recovery of lithium from spent lithium-ion batteries by reduction roasting and NaHCO3 leaching.

Lithium supply risk is increasing and driving rapid progress in lithium recovery schemes from spent lithium-ion batteries (LIBs). In this study, a facile recycling process consisting mainly of reduction roasting and NaHCO3 leaching was adopted to improve lithium recovery. The Li of spent LiNixCoyMn1-x-yO2 powder were converted to Li2CO3 and LiAlO2 with the reduction effect of C and residual Al in the roasting process. NaHCO3 leaching was utilized to selectively dissolve lithium from Li2CO3 and water-insoluble LiAlO2. The activation energy of NaHCO3 leaching was 9.31 kJ∙mol-1 and the leaching of lithium was a diffusion control reaction. More than 95.19 % lithium was leached and recovered as a Li2CO3 product with a purity of 99.80 %. Thus, this approach provides a green path to selective recovery of lithium with good economics.

Modulation of GPR133 (ADGRD1) signaling by its intracellular interaction partner extended synaptotagmin 1.

GPR133 (ADGRD1) is an adhesion G-protein-coupled receptor that signals through Gαs/cyclic AMP (cAMP) and is required for the growth of glioblastoma (GBM), an aggressive brain malignancy. The regulation of GPR133 signaling is incompletely understood. Here, we use proximity biotinylation proteomics to identify ESYT1, a Ca2+-dependent mediator of endoplasmic reticulum-plasma membrane bridge formation, as an intracellular interactor of GPR133. ESYT1 knockdown or knockout increases GPR133 signaling, while its overexpression has the opposite effect, without altering GPR133 levels in the plasma membrane. The GPR133-ESYT1 interaction requires the Ca2+-sensing C2C domain of ESYT1. Thapsigargin-mediated increases in cytosolic Ca2+ relieve signaling-suppressive effects of ESYT1 by promoting ESYT1-GPR133 dissociation. ESYT1 knockdown or knockout in GBM slows tumor growth, suggesting tumorigenic functions of ESYT1. Our findings demonstrate a mechanism for the modulation of GPR133 signaling by increased cytosolic Ca2+, which reduces the signaling-suppressive interaction between GPR133 and ESYT1 to raise cAMP levels.

Exploring the molecular mechanism of Xuebifang in the treatment of diabetic peripheral neuropathy based on bioinformatics and network pharmacology.

Background: Xuebifang (XBF), a potent Chinese herbal formula, has been employed in managing diabetic peripheral neuropathy (DPN). Nevertheless, the precise mechanism of its action remains enigmatic. Purpose: The primary objective of this investigation is to employ a bioinformatics-driven approach combined with network pharmacology to comprehensively explore the therapeutic mechanism of XBF in the context of DPN. Study design and Methods: The active chemicals and their respective targets of XBF were sourced from the TCMSP and BATMAN databases. Differentially expressed genes (DEGs) related to DPN were obtained from the GEO database. The targets associated with DPN were compiled from the OMIM, GeneCards, and DrugBank databases. The analysis of GO, KEGG pathway enrichment, as well as immuno-infiltration analysis, was conducted using the R language. The investigation focused on the distribution of therapeutic targets of XBF within human organs or cells. Subsequently, molecular docking was employed to evaluate the interactions between potential targets and active compounds of XBF concerning the treatment of DPN. Results: The study successfully identified a total of 122 active compounds and 272 targets associated with XBF. 5 core targets of XBF for DPN were discovered by building PPI network. According to GO and KEGG pathway enrichment analysis, the mechanisms of XBF for DPN could be related to inflammation, immune regulation, and pivotal signalling pathways such as the TNF, TLR, CLR, and NOD-like receptor signalling pathways. These findings were further supported by immune infiltration analysis and localization of immune organs and cells. Moreover, the molecular docking simulations demonstrated a strong binding affinity between the active chemicals and the carefully selected targets. Conclusion: In summary, this study proposes a novel treatment model for XBF in DPN, and it also offers a new perspective for exploring the principles of traditional Chinese medicine (TCM) in the clinical management of DPN.

Side Lighting of Red, Blue and Green Spectral Combinations Altered the Growth, Yield and Quality of Lettuce (Lactuca sativa L. cv. "Yidali") in Plant Factory.

A plant factory with artificial lighting (PFAL) usually uses top lighting for cultivation. The light from the upper part of the canopy cannot penetrate the entire lettuce canopy, however, resulting in uneven vertical spatial light in the canopy, and accelerating the senescence of both the bottom and side leaves of the plant canopy. Therefore, in this study, the performance of lettuce in hydroponics was investigated upon supplemental side lighting with different spectral LEDs in a PFAL. A set of short-term side lighting treatments, including no side lamps (CK), red (R), blue (B), red + blue (RB), and red + blue + green (RGB) LED lamps (150 µmol·m-2·s-1, respectively), was employed for an additional 2 h per day after normal top lighting for 6 days before harvest. The results showed that the lettuce canopy was relatively loose and had a large crown size under side lighting compared with CK. Side lighting, irrespective of spectral qualities, significantly increased the fresh weight, and the R, B, RB, and RGB treatments increased the shoot fresh weight of lettuce plants by 34%, 19%, 31%, and 34%, and increased the fresh weight of leaf layer 2 by 50%, 17%, 44%, and 48%, respectively. The side lighting of different spectral qualities had a significant impact on the nutritional quality of the first row of lettuce at the edge of the top lighting illuminated area. Treatment B significantly promoted the chlorophyll content of leaf layer 3; the soluble sugar contents from leaf layer 1, 2, and 3; the starch contents in leaf layers 2 and 3; and the content of phenolics in the leaf layers 3; and significantly reduced the nitrate content in leaf layers 2 and 3. RGB significantly increased soluble sugar content by 91%, and the starch content in leaf layer 1, as well as the leaf chlorophyll and flavonoid content of leaf layer 3, while R had opposite effect completely. RB significantly increased the leaf chlorophyll content of leaf layer 3 and the nitrate content in leaf layer 1, but the overall effect was lower than that of RGB. In summary, side lighting of any type could effectively improve lettuce yield, solve the problem of inconsistent lettuce plant size caused by the edge effect of top lighting, and affect the nutritional quality of lettuce. B and RGB performed best. There was spatial response diversity of lettuce plants to side lighting spectral qualities.

The Biological and Regulatory Role of Type VI Secretion System of Klebsiella pneumoniae.

Bacteria communicate with their surroundings through diverse secretory systems, and the recently discovered Type VI Secretion System (T6SS) has gained significant attention. Klebsiella pneumoniae (K. pneumoniae), an opportunistic pathogen known for causing severe infections in both hospital and animal settings, possesses this intriguing T6SS. This system equips K. pneumoniae with a formidable armory of protein-based weaponry, enabling the delivery of toxins into neighboring cells, thus granting a substantial competitive advantage. Remarkably, the T6SS has also been associated with K. pneumoniae's ability to form biofilms and acquire resistance against antibiotics. However, the precise effects of the T6SS on K. pneumoniae's functions remain inadequately studied, despite research efforts to understand the intricacies of these mechanisms. This comprehensive review aims to provide an overview of the current knowledge regarding the biological functions and regulatory mechanisms of the T6SS in K. pneumoniae.

High-Proportion Blue Light Irradiation at the End-of-Production Stage Promotes the Biosynthesis and Recycling of Ascorbate in Lettuce.

Ascorbate (AsA), an essential antioxidant for both plants and the human body, plays a vital role in maintaining proper functionality. Light plays an important role in metabolism of AsA in horticultural plants. Our previous research has revealed that subjecting lettuce to high light irradiation (HLI) (500 µmol·m-2·s-1) at the end-of-production (EOP) stage effectively enhances AsA levels, while the optimal light quality for AsA accumulation is still unknown. In this study, four combinations of red (R) and blue (B) light spectra with the ratio of 1:1 (1R1B), 2:1 (2R1B), 3:1 (3R1B), and 4:1 (4R1B) were applied to investigate the biosynthesis and recycling of AsA in lettuce. The results demonstrated that the AsA/total-AsA content in lettuce leaves was notably augmented upon exposure to 1R1B and 2R1B. Interestingly, AsA levels across all treatments increased rapidly at the early stage (2-8 h) of irradiation, while they increased slowly at the late stage (8-16 h). The activity of L-galactono-1,4-lactone dehydrogenase was augmented under 1R1B treatment, which is pivotal to AsA production. Additionally, the activities of enzymes key to AsA cycling were enhanced by 1R1B and 2R1B treatments, including ascorbate peroxidase, dehydroascorbate reductase, and monodehydroascorbate reductase. Notably, hydrogen peroxide and malondialdehyde accumulation increased dramatically following 16 h of 1R1B and 2R1B treatments. In addition, although soluble sugar and starch contents were enhanced by EOP-HLI, this effect was comparatively subdued under the 1R1B treatment. Overall, these results indicated that AsA accumulation was improved by irradiation with a blue light proportion of over 50% in lettuce, aligning with the heightened activities of key enzymes responsible for AsA synthesis, as well as the accrual of hydrogen peroxide. The effective strategy holds the potential to enhance the nutritional quality of lettuce while bolstering its antioxidant defenses.

Polysaccharide-Based Composite Hydrogel with Hierarchical Microstructure for Enhanced Vascularization and Skull Regeneration.

Critical-size skull defects caused by trauma, infection, and tumor resection raise great demands for efficient bone substitutes. Herein, a hybrid cross-linked hierarchical microporous hydrogel scaffold (PHCLS) was successfully assembled by a multistep procedure, which involved (i) the preparation of poly(lactic-co-glycolic)/nanohydroxyapatite (PLGA-HAP) porous microspheres, (ii) embedding the spheres in a solution of dopamine-modified hyaluronic acid and collagen I (Col I) and cross-linking via dopamine polyphenols binding to (i) Col I amino groups (via Michael addition) and (ii) PLGA-HAP (via calcium ion chelation). The introduction of PLGA-HAP not only improved the diversity of pore size and pore communication inside the matrix but also greatly enhanced the compressive strength (5.24-fold, 77.5 kPa) and degradation properties to construct a more stable mechanical structure. In particular, the PHCLS (200 mg, nHAP) promoted the proliferation, infiltration, and angiogenic differentiation of bone marrow mesenchymal stem cells in vitro, as well as significant ectopic angiogenesis and mineralization with a storage modulus enhancement of 2.5-fold after 30 days. Meanwhile, the appropriate matrix microenvironment initiated angiogenesis and early osteogenesis by accelerating endogenous stem cell recruitment in situ. Together, the PHCLS allowed substantial skull reconstruction in the rabbit cranial defect model, achieving 85.2% breaking load strength and 84.5% bone volume fractions in comparison to the natural cranium, 12 weeks after implantation. Overall, this study reveals that the hierarchical microporous hydrogel scaffold provides a promising strategy for skull defect treatment.

Pan-cancer proteogenomics connects oncogenic drivers to functional states.

Cancer driver events refer to key genetic aberrations that drive oncogenesis; however, their exact molecular mechanisms remain insufficiently understood. Here, our multi-omics pan-cancer analysis uncovers insights into the impacts of cancer drivers by identifying their significant cis-effects and distal trans-effects quantified at the RNA, protein, and phosphoprotein levels. Salient observations include the association of point mutations and copy-number alterations with the rewiring of protein interaction networks, and notably, most cancer genes converge toward similar molecular states denoted by sequence-based kinase activity profiles. A correlation between predicted neoantigen burden and measured T cell infiltration suggests potential vulnerabilities for immunotherapies. Patterns of cancer hallmarks vary by polygenic protein abundance ranging from uniform to heterogeneous. Overall, our work demonstrates the value of comprehensive proteogenomics in understanding the functional states of oncogenic drivers and their links to cancer development, surpassing the limitations of studying individual cancer types.

Deep learning integrates histopathology and proteogenomics at a pan-cancer level.

We introduce a pioneering approach that integrates pathology imaging with transcriptomics and proteomics to identify predictive histology features associated with critical clinical outcomes in cancer. We utilize 2,755 H&E-stained histopathological slides from 657 patients across 6 cancer types from CPTAC. Our models effectively recapitulate distinctions readily made by human pathologists: tumor vs. normal (AUROC = 0.995) and tissue-of-origin (AUROC = 0.979). We further investigate predictive power on tasks not normally performed from H&E alone, including TP53 prediction and pathologic stage. Importantly, we describe predictive morphologies not previously utilized in a clinical setting. The incorporation of transcriptomics and proteomics identifies pathway-level signatures and cellular processes driving predictive histology features. Model generalizability and interpretability is confirmed using TCGA. We propose a classification system for these tasks, and suggest potential clinical applications for this integrated human and machine learning approach. A publicly available web-based platform implements these models.

Proteogenomic insights suggest druggable pathways in endometrial carcinoma.

We characterized a prospective endometrial carcinoma (EC) cohort containing 138 tumors and 20 enriched normal tissues using 10 different omics platforms. Targeted quantitation of two peptides can predict antigen processing and presentation machinery activity, and may inform patient selection for immunotherapy. Association analysis between MYC activity and metformin treatment in both patients and cell lines suggests a potential role for metformin treatment in non-diabetic patients with elevated MYC activity. PIK3R1 in-frame indels are associated with elevated AKT phosphorylation and increased sensitivity to AKT inhibitors. CTNNB1 hotspot mutations are concentrated near phosphorylation sites mediating pS45-induced degradation of ß-catenin, which may render Wnt-FZD antagonists ineffective. Deep learning accurately predicts EC subtypes and mutations from histopathology images, which may be useful for rapid diagnosis. Overall, this study identified molecular and imaging markers that can be further investigated to guide patient stratification for more precise treatment of EC.

PTK7 is a positive allosteric modulator of GPR133 signaling in glioblastoma.

The adhesion G-protein-coupled receptor GPR133 (ADGRD1) supports growth of the brain malignancy glioblastoma. How the extracellular interactome of GPR133 in glioblastoma modulates signaling remains unknown. Here, we use affinity proteomics to identify the transmembrane protein PTK7 as an extracellular binding partner of GPR133 in glioblastoma. PTK7 binds the autoproteolytically generated N-terminal fragment of GPR133 and its expression in trans increases GPR133 signaling. This effect requires the intramolecular cleavage of GPR133 and PTK7's anchoring in the plasma membrane. PTK7's allosteric action on GPR133 signaling is additive with but topographically distinct from orthosteric activation by soluble peptide mimicking the endogenous tethered Stachel agonist. GPR133 and PTK7 are expressed in adjacent cells in glioblastoma, where their knockdown phenocopies each other. We propose that this ligand-receptor interaction is relevant to the pathogenesis of glioblastoma and possibly other physiological processes in healthy tissues.

Modulation of GPR133 (ADGRD1) Signaling by its Intracellular Interaction Partner Extended Synaptotagmin 1 (ESYT1).

GPR133 (ADGRD1) is an adhesion G protein-coupled receptor that signals through Gαs and is required for growth of glioblastoma (GBM), an aggressive brain malignancy. The regulation of GPR133 signaling is incompletely understood. Here, we use proximity biotinylation proteomics to identify ESYT1, a Ca2+-dependent mediator of endoplasmic reticulum-plasma membrane bridge formation, as an intracellular interactor of GPR133. ESYT1 knockdown or knockout increases GPR133 signaling, while its overexpression has the opposite effect, without altering GPR133 levels in the plasma membrane. The GPR133-ESYT1 interaction requires the Ca2+-sensing C2C domain of ESYT1. Thapsigargin-mediated increases in cytosolic Ca2+ relieve signaling-suppressive effects of ESYT1 by promoting ESYT1-GPR133 dissociation. ESYT1 knockdown or knockout in GBM impairs tumor growth in vitro, suggesting functions of ESYT1 beyond the interaction with GPR133. Our findings suggest a novel mechanism for modulation of GPR133 signaling by increased cytosolic Ca2+, which reduces the signaling-suppressive interaction between GPR133 and ESYT1 to raise cAMP levels.

Histopathologic and proteogenomic heterogeneity reveals features of clear cell renal cell carcinoma aggressiveness.

Clear cell renal cell carcinomas (ccRCCs) represent ∼75% of RCC cases and account for most RCC-associated deaths. Inter- and intratumoral heterogeneity (ITH) results in varying prognosis and treatment outcomes. To obtain the most comprehensive profile of ccRCC, we perform integrative histopathologic, proteogenomic, and metabolomic analyses on 305 ccRCC tumor segments and 166 paired adjacent normal tissues from 213 cases. Combining histologic and molecular profiles reveals ITH in 90% of ccRCCs, with 50% demonstrating immune signature heterogeneity. High tumor grade, along with BAP1 mutation, genome instability, increased hypermethylation, and a specific protein glycosylation signature define a high-risk disease subset, where UCHL1 expression displays prognostic value. Single-nuclei RNA sequencing of the adverse sarcomatoid and rhabdoid phenotypes uncover gene signatures and potential insights into tumor evolution. In vitro cell line studies confirm the potential of inhibiting identified phosphoproteome targets. This study molecularly stratifies aggressive histopathologic subtypes that may inform more effective treatment strategies.

Surgical Treatment of Pineal Region Tumors: An 18 year-Experience at a Single Institution.

BACKGROUND: The pineal tumor was once considered as a restricted area for surgery. Such cases are rare, with many different opinions on surgical treatment. This study aimed to review our experience of tumor treatment in the pineal region and explore the optimal treatment strategy. METHODS: The clinical data of 72 patients with pineal tumors from January 1997 to May 2015 (18 years) were retrospectively analyzed. Preoperative preparation, pathology type, tumor resection rate, surgical approach, and follow-up outcomes were used as the indicators to evaluate the treatment efficacy. RESULTS: The Krause approach was used in 46 cases, the Poppen approach in 10 cases, and the transcallosal-lateral ventricle-choroid fissure approach in 16 cases. The postoperative pathological results were as follows: 24 cases of germinoma, 11 of teratoma, 15 of glioma, 6 of meningioma, 11 of Pineocytoma, 2 of cholesteatoma, 2 of cavernous hemangioma, and 1 of choriocarcinoma. Further, the study included 64 cases of total surgical resections, 8 of subtotal resections, and 2 deaths. The follow-up period was from 7 months to 10 years. Further, 51 (70.8%) patients were followed up. The multivariate regression model showed that the surgical method and the pathological type contributed significantly to predicting outcomes. CONCLUSIONS: The type of pathology, extent of excision, and surgical approach had a significant impact on the prognosis of patients. The transcallosal-lateral ventricle-choroid fissure approach for large and medium-sized pineal tumors near the posterior part of the third ventricle had good efficacy.

Effect of natural polyphenols in Chinese herbal medicine on obesity and diabetes: Interactions among gut microbiota, metabolism, and immunity.

With global prevalence, metabolic diseases, represented by obesity and type 2 diabetes mellitus (T2DM), have a huge burden on human health and medical expenses. It is estimated that obese population has doubled in recent 40 years, and population with diabetes will increase 1.5 times in next 25 years, which has inspired the pursuit of economical and effective prevention and treatment methods. Natural polyphenols are emerging as a class of natural bioactive compounds with potential beneficial effects on the alleviation of obesity and T2DM. In this review, we investigated the network interaction mechanism of "gut microbial disturbance, metabolic disorder, and immune imbalance" in both obesity and T2DM and systemically summarized their multiple targets in the treatment of obesity and T2DM, including enrichment of the beneficial gut microbiota (genera Bifidobacterium, Akkermansia, and Lactobacillus) and upregulation of the levels of gut microbiota-derived metabolites [short-chain fatty acids (SCFAs)] and bile acids (BAs). Moreover, we explored their effect on host glucolipid metabolism, the AMPK pathway, and immune modulation via the inhibition of pro-inflammatory immune cells (M1-like Mϕs, Th1, and Th17 cells); proliferation, recruitment, differentiation, and function; and related cytokines (TNF-α, IL-1ß, IL-6, IL-17, and MCP-1). We hope to provide evidence to promote the clinical application of natural polyphenols in the management of obesity and T2DM.

Brain structural network to investigate the mechanism of cognitive impairment in patients with acoustic neuroma.

Objective: Acoustic neuroma (AN) is a common benign tumor. Little is known of neuropsychological studies in patients with acoustic neuroma, especially cognitive neuropsychology, and the neuropsychological abnormalities of patients affect their life quality. The purpose of this study was to explore the changes in the cognitive function of patients with acoustic neuroma, and the possible mechanism of these changes by structural magnetic resonance imaging. Materials and methods: We used a neuropsychological assessment battery to assess cognitive function in 69 patients with acoustic neuroma and 70 healthy controls. Then, we used diffusion tensor imaging data to construct the structural brain network and calculate topological properties based on graph theory, and we studied the relation between the structural brain network and cognitive function. Moreover, three different subnetworks (short-range subnetwork, middle-range subnetwork, and long-range subnetwork) were constructed by the length of nerve fibers obtained from deterministic tracking. We studied the global and local efficiency of various subnetworks and analyzed the correlation between network metrics and cognitive function. Furthermore, connectome edge analysis directly assessed whether there were differences in the number of fibers in the different brain regions. We analyzed the relation between the differences and cognitive function. Results: Compared with the healthy controls, the general cognitive function, memory, executive function, attention, visual space executive ability, visual perception ability, movement speed, and information processing speed decreased significantly in patients with acoustic neuroma. A unilateral hearing loss due to a left acoustic neuroma had a greater impact on cognitive function. The results showed that changes in the global and local metrics, the efficiency of subnetworks, and cognitively-related fiber connections were associated with cognitive impairments in patients with acoustic neuroma. Conclusion: Patients exhibit cognitive impairments caused by the decline of the structure and function in some brain regions, and they also develop partial compensation after cognitive decline. Cognitive problems are frequent in patients with acoustic neuroma. Including neuropsychological aspects in the routine clinical evaluation and appropriate treatments may enhance the clinical management and improve their life quality.

Baseline Serum Autoantibody Signatures Predict Recurrence and Toxicity in Melanoma Patients Receiving Adjuvant Immune Checkpoint Blockade.

PURPOSE: Adjuvant immunotherapy produces durable benefit for patients with resected melanoma, but many develop recurrence and/or immune-related adverse events (irAE). We investigated whether baseline serum autoantibody (autoAb) signatures predicted recurrence and severe toxicity in patients treated with adjuvant nivolumab, ipilimumab, or ipilimumab plus nivolumab. EXPERIMENTAL DESIGN: This study included 950 patients: 565 from CheckMate 238 (408 ipilimumab versus 157 nivolumab) and 385 from CheckMate 915 (190 nivolumab versus 195 ipilimumab plus nivolumab). Serum autoAbs were profiled using the HuProt Human Proteome Microarray v4.0 (CDI Laboratories, Mayaguez, PR). Analysis of baseline differentially expressed autoAbs was followed by recurrence and severe toxicity signature building for each regimen, testing of the signatures, and additional independent validation for nivolumab using patients from CheckMate 915. RESULTS: In the nivolumab independent validation cohort, high recurrence score predicted significantly worse recurrence-free survival [RFS; adjusted HR (aHR), 3.60; 95% confidence interval (CI), 1.98-6.55], and outperformed a model composed of clinical variables including PD-L1 expression (P < 0.001). Severe toxicity score was a significant predictor of severe irAEs (aHR, 13.53; 95% CI, 2.59-86.65). In the ipilimumab test cohort, high recurrence score was associated with significantly worse RFS (aHR, 3.21; 95% CI, 1.38-7.45) and severe toxicity score significantly predicted severe irAEs (aHR, 11.04; 95% CI, 3.84-37.25). In the ipilimumab plus nivolumab test cohort, high autoAb recurrence score was associated with significantly worse RFS (aHR, 6.45; 95% CI, 1.48-28.02), and high severe toxicity score was significantly associated with severe irAEs (aHR, 23.44; 95% CI, 4.10-212.50). CONCLUSIONS: Baseline serum autoAb signatures predicted recurrence and severe toxicity in patients treated with adjuvant immunotherapy. Prospective testing of the signatures that include datasets with longer follow-up and rare but more severe toxicities will help determine their generalizability and potential clinical utility. See related commentary by Hassel and Luke, p. 3914.

Molecular Characterization of Klebsiella pneumoniae Isolated from Sputum in a Tertiary Hospital in Xinxiang, China.

Background: In clinical practice, Klebsiella pneumoniae (K. pneumoniae) is a common opportunistic pathogen responsible for nosocomial infection. This study aimed to analyze the trend of antimicrobial susceptibility and virulent characteristics of K. pneumoniae isolated from sputum. In clinics, data of the current study will help in the clinical treatment of K. pneumoniae infection. Results: The current research showed the resistance rates of the 20 K. pneumoniae isolates against 13 antibiotics ranged from 15.0% to 80.0%. The detection rate of extended spectrum ß-lactamases (ESBLs) was up to 55%, while blaSHV was the most prevalent ESBLs genes. Four strains (25.0%) of K. pneumoniae presented hypermucoviscous phenotype (HMV). Moreover, 18 strains (90.0%) showed the stronger biofilm-forming ability. wzi, wabG, fimH, mrkD were the most prevalent virulence genes in current research. Ten strains were found capsule typing and the higher genetic diversity of colonizing K. pneumoniae in this region. K19 exhibited a strong positive correlation with imipenem resistance, while K1 showed strong correlations with magA . Furthermore, HMV phenotype showed significantly negative correlations with multidrug-resistant. Conclusion: In the hospital, the antibiotic resistance of K. pneumoniae (isolated from sputum samples) has a serious concern. Additionally, strains of K. pneumoniae show the higher genetic diversity.

Prediction of Maternal Hemorrhage Using Machine Learning: Retrospective Cohort Study.

BACKGROUND: Postpartum hemorrhage remains one of the largest causes of maternal morbidity and mortality in the United States. OBJECTIVE: The aim of this paper is to use machine learning techniques to identify patients at risk for postpartum hemorrhage at obstetric delivery. METHODS: Women aged 18 to 55 years delivering at a major academic center from July 2013 to October 2018 were included for analysis (N=30,867). A total of 497 variables were collected from the electronic medical record including the following: demographic information; obstetric, medical, surgical, and family history; vital signs; laboratory results; labor medication exposures; and delivery outcomes. Postpartum hemorrhage was defined as a blood loss of ≥1000 mL at the time of delivery, regardless of delivery method, with 2179 (7.1%) positive cases observed. Supervised learning with regression-, tree-, and kernel-based machine learning methods was used to create classification models based upon training (21,606/30,867, 70%) and validation (4630/30,867, 15%) cohorts. Models were tuned using feature selection algorithms and domain knowledge. An independent test cohort (4631/30,867, 15%) determined final performance by assessing for accuracy, area under the receiver operating curve (AUROC), and sensitivity for proper classification of postpartum hemorrhage. Separate models were created using all collected data versus models limited to data available prior to the second stage of labor or at the time of decision to proceed with cesarean delivery. Additional models examined patients by mode of delivery. RESULTS: Gradient boosted decision trees achieved the best discrimination in the overall model. The model including all data mildly outperformed the second stage model (AUROC 0.979, 95% CI 0.971-0.986 vs AUROC 0.955, 95% CI 0.939-0.970). Optimal model accuracy was 98.1% with a sensitivity of 0.763 for positive prediction of postpartum hemorrhage. The second stage model achieved an accuracy of 98.0% with a sensitivity of 0.737. Other selected algorithms returned models that performed with decreased discrimination. Models stratified by mode of delivery achieved good to excellent discrimination but lacked the sensitivity necessary for clinical applicability. CONCLUSIONS: Machine learning methods can be used to identify women at risk for postpartum hemorrhage who may benefit from individualized preventative measures. Models limited to data available prior to delivery perform nearly as well as those with more complete data sets, supporting their potential utility in the clinical setting. Further work is necessary to create successful models based upon mode of delivery and to validate the findings of this study. An unbiased approach to hemorrhage risk prediction may be superior to human risk assessment and represents an area for future research.

Systematic analysis of the sugar accumulation mechanism in sucrose- and hexose- accumulating cherry tomato fruits.

BACKGROUND: Sugar content is an important indicator of fruit quality. Except for a few wild tomato species that accumulate sucrose in the fruits, most cultivated tomato species accumulate hexose. Although several studies have focused on wild sucrose-accumulating tomato, the sucrose accumulation mechanism is still unclear. RESULTS: Here, two homozygous inbred cherry tomato lines ('TB0023' and 'TB0278', which accumulated sucrose and hexose, respectively) were selected to analyze the sugar accumulation mechanism. Carbohydrate analysis, cytological observation, gene expression and enzyme activity analysis and proteomics methods were used in this study. The results indicated that glucose and fructose were absolutely dominant in the soluble sugar content of hexose-accumulating cherry tomato fruit, while sucrose and a certain proportion of hexose were the main forms of soluble sugar in sucrose-accumulating cherry tomato fruit. The phloem unloading pathway of the hexose-accumulating cherry tomato fruit switched from symplastic to apoplastic during fruit development, and the sucrose-accumulating cherry tomato probably had a mixed unloading pathway involving the symplastic and apoplastic. High activity of acid invertase (AI), sucrose phosphate synthase (SPS), sucrose synthase (SS) and sugar transporters LeSUT1, SlSWEET2a and SlSWEET12c were important factors for hexose accumulation in the hexose-accumulating cherry tomato fruit, while LeSUT2, SPS, SS, SlSWEET1b, SlSWEET5b, SlSWEET11b, SlSWEET7a, SlSWEET14 were responsible for solute sugar accumulation in the sucrose-accumulating cherry tomato. CONCLUSIONS: This study provides detailed evidence for elucidation of the tomato sugar accumulation mechanism from the perspective of cell structure, physiology and molecular biology, providing a theoretical basis for the improvement of tomato quality and aiding the utilization of tomato genetic resources.