The TOR-EIN2 axis mediates nuclear signalling to modulate plant growth.

The evolutionarily conserved target of rapamycin (TOR) kinase acts as a master regulator that coordinates cell proliferation and growth by integrating nutrient, energy, hormone and stress signals in all eukaryotes1,2. Research has focused mainly on TOR-regulated translation, but how TOR orchestrates the global transcriptional network remains unclear. Here we identify ethylene-insensitive protein 2 (EIN2), a central integrator3-5 that shuttles between the cytoplasm and the nucleus, as a direct substrate of TOR in Arabidopsis thaliana. Glucose-activated TOR kinase directly phosphorylates EIN2 to prevent its nuclear localization. Notably, the rapid global transcriptional reprogramming that is directed by glucose-TOR signalling is largely compromised in the ein2-5 mutant, and EIN2 negatively regulates the expression of a wide range of target genes of glucose-activated TOR that are involved in DNA replication, cell wall and lipid synthesis and various secondary metabolic pathways. Chemical, cellular and genetic analyses reveal that cell elongation and proliferation processes that are controlled by the glucose-TOR-EIN2 axis are decoupled from canonical ethylene-CTR1-EIN2 signalling, and mediated by different phosphorylation sites. Our findings reveal a molecular mechanism by which a central signalling hub is shared but differentially modulated by diverse signalling pathways using distinct phosphorylation codes that can be specified by upstream protein kinases.

CropGS-Hub: a comprehensive database of genotype and phenotype resources for genomic prediction in major crops.

The explosive amount of multi-omics data has brought a paradigm shift both in academic research and further application in life science. However, managing and reusing the growing resources of genomic and phenotype data points presents considerable challenges for the research community. There is an urgent need for an integrated database that combines genome-wide association studies (GWAS) with genomic selection (GS). Here, we present CropGS-Hub, a comprehensive database comprising genotype, phenotype, and GWAS signals, as well as a one-stop platform with built-in algorithms for genomic prediction and crossing design. This database encompasses a comprehensive collection of over 224 billion genotype data and 434 thousand phenotype data generated from >30 000 individuals in 14 representative populations belonging to 7 major crop species. Moreover, the platform implemented three complete functional genomic selection related modules including phenotype prediction, user model training and crossing design, as well as a fast SNP genotyper plugin-in called SNPGT specifically built for CropGS-Hub, aiming to assist crop scientists and breeders without necessitating coding skills. CropGS-Hub can be accessed at https://iagr.genomics.cn/CropGS/.

Integration of transcriptomics, metabolomics, and hormone analysis revealed the formation of lesion spots inhibited by GA and CTK was related to cell death and disease resistance in bread wheat (Triticum aestivum L.).

BACKGROUND: Wheat is one of the important grain crops in the world. The formation of lesion spots related to cell death is involved in disease resistance, whereas the regulatory pathway of lesion spot production and resistance mechanism to pathogens in wheat is largely unknown. RESULTS: In this study, a pair of NILs (NIL-Lm5W and NIL-Lm5M) was constructed from the BC1F4 population by the wheat lesion mimic mutant MC21 and its wild genotype Chuannong 16. The formation of lesion spots in NIL-Lm5M significantly increased its resistance to stripe rust, and NIL-Lm5M showed superiour agronomic traits than NIL-Lm5W under stripe rust infection.Whereafter, the NILs were subjected to transcriptomic (stage N: no spots; stage S, only a few spots; and stage M, numerous spots), metabolomic (stage N and S), and hormone analysis (stage S), with samples taken from normal plants in the field. Transcriptomic analysis showed that the differentially expressed genes were enriched in plant-pathogen interaction, and defense-related genes were significantly upregulated following the formation of lesion spots. Metabolomic analysis showed that the differentially accumulated metabolites were enriched in energy metabolism, including amino acid metabolism, carbohydrate metabolism, and lipid metabolism. Correlation network diagrams of transcriptomic and metabolomic showed that they were both enriched in energy metabolism. Additionally, the contents of gibberellin A7, cis-Zeatin, and abscisic acid were decreased in leaves upon lesion spot formation, whereas the lesion spots in NIL-Lm5M leaves were restrained by spaying GA and cytokinin (CTK, trans-zeatin) in the field. CONCLUSION: The formation of lesion spots can result in cell death and enhance strip rust resistance by protein degradation pathway and defense-related genes overexpression in wheat. Besides, the formation of lesion spots was significantly affected by GA and CTK. Altogether, these results may contribute to the understanding of lesion spot formation in wheat and laid a foundation for regulating the resistance mechanism to stripe rust.

Preoperative Differentiation of HER2-Zero and HER2-Low from HER2-Positive Invasive Ductal Breast Cancers Using BI-RADS MRI Features and Machine Learning Modeling.

BACKGROUND: Accurate determination of human epidermal growth factor receptor 2 (HER2) is important for choosing optimal HER2 targeting treatment strategies. HER2-low is currently considered HER2-negative, but patients may be eligible to receive new anti-HER2 drug conjugates. PURPOSE: To use breast MRI BI-RADS features for classifying three HER2 levels, first to distinguish HER2-zero from HER2-low/positive (Task-1), and then to distinguish HER2-low from HER2-positive (Task-2). STUDY TYPE: Retrospective. POPULATION: 621 invasive ductal cancer, 245 HER2-zero, 191 HER2-low, and 185 HER2-positive. For Task-1, 488 cases for training and 133 for testing. For Task-2, 294 cases for training and 82 for testing. FIELD STRENGTH/SEQUENCE: 3.0 T; 3D T1-weighted DCE, short time inversion recovery T2, and single-shot EPI DWI. ASSESSMENT: Pathological information and BI-RADS features were compared. Random Forest was used to select MRI features, and then four machine learning (ML) algorithms: decision tree (DT), support vector machine (SVM), k-nearest neighbors (k-NN), and artificial neural nets (ANN), were applied to build models. STATISTICAL TESTS: Chi-square test, one-way analysis of variance, and Kruskal-Wallis test were performed. The P values <0.05 were considered statistically significant. For ML models, the generated probability was used to construct the ROC curves. RESULTS: Peritumoral edema, the presence of multiple lesions and non-mass enhancement (NME) showed significant differences. For distinguishing HER2-zero from non-zero (low + positive), multiple lesions, edema, margin, and tumor size were selected, and the k-NN model achieved the highest AUC of 0.86 in the training set and 0.79 in the testing set. For differentiating HER2-low from HER2-positive, multiple lesions, edema, and margin were selected, and the DT model achieved the highest AUC of 0.79 in the training set and 0.69 in the testing set. DATA CONCLUSION: BI-RADS features read by radiologists from preoperative MRI can be analyzed using more sophisticated feature selection and ML algorithms to build models for the classification of HER2 status and identify HER2-low. TECHNICAL EFFICACY: Stage 2.

A co-located QTL for seven spike architecture-related traits shows promising breeding use potential in common wheat (Triticum aestivum L.).

KEY MESSAGE: A co-located novel QTL for TFS, FPs, FMs, FFS, FFPs, KWS, and KWPs with potential of improving wheat yield was identified and validated. Spike-related traits, including fertile florets per spike (FFS), kernel weight per spike (KWS), total florets per spike (TFS), florets per spikelet (FPs), florets in the middle spikelet (FMs), fertile florets per spikelet (FFPs), and kernel weight per spikelet (KWPs), are key traits in improving wheat yield. In the present study, quantitative trait loci (QTL) for these traits evaluated under various environments were detected in a recombinant inbred line population (msf/Chuannong 16) mainly genotyped using the 16 K SNP array. Ultimately, we identified 60 QTL, but only QFFS.sau-MC-1A for FFS was a major and stably expressed QTL. It was located on chromosome arm 1AS, where loci for TFS, FPs, FMs, FFS, FFPs, KWS, and KWPs were also simultaneously co-mapped. The effect of QFFS.sau-MC-1A was further validated in three independent segregating populations using a Kompetitive Allele-Specific PCR marker. For the co-located QTL, QFFS.sau-MC-1A, the presence of a positive allele from msf was associate with increases for all traits: + 12.29% TFS, + 10.15% FPs, + 13.97% FMs, + 17.12% FFS, + 14.75% FFPs, + 22.17% KWS, and + 19.42% KWPs. Furthermore, pleiotropy analysis showed that the positive allele at QFFS.sau-MC-1A simultaneously increased the spike length, spikelet number per spike, and thousand-kernel weight. QFFS.sau-MC-1A represents a novel QTL for marker-assisted selection with the potential for improving wheat yield. Four genes, TraesCS1A03G0012700, TraesCS1A03G0015700, TraesCS1A03G0016000, and TraesCS1A03G0016300, which may affect spike development, were predicted in the physical interval harboring QFFS.sau-MC-1A. Our results will help in further fine mapping QFFS.sau-MC-1A and be useful for improving wheat yield.

Indoxyl sulphate-TNFα axis mediates uremic encephalopathy in rodent acute kidney injury.

Acute kidney injury (AKI) is often accompanied by uremic encephalopathy resulting from accumulation of uremic toxins in brain possibly due to impaired blood-brain barrier (BBB) function. Anionic uremic toxins are substrates or inhibitors of organic anionic transporters (OATs). In this study we investigated the CNS behaviors and expression/function of BBB OAT3 in AKI rats and mice, which received intraperitoneal injection of cisplatin 8 and 20 mg/kg, respectively. We showed that cisplatin treatment significantly inhibited the expressions of OAT3, synaptophysin and microtubule-associated protein 2 (MAP2), impaired locomotor and exploration activities, and increased accumulation of uremic toxins in the brain of AKI rats and mice. In vitro studies showed that uremic toxins neither alter OAT3 expression in human cerebral microvascular endothelial cells, nor synaptophysin and MAP2 expressions in human neuroblastoma (SH-SY5Y) cells. In contrast, tumour necrosis factor alpha (TNFα) and the conditioned medium (CM) from RAW264.7 cells treated with indoxyl sulfate (IS) significantly impaired OAT3 expression. TNFα and CM from IS-treated BV-2 cells also inhibited synaptophysin and MAP2 expressions in SH-SY5Y cells. The alterations caused by TNFα and CMs in vitro, and by AKI and TNFα in vivo were abolished by infliximab, a monoclonal antibody designed to intercept and neutralize TNFα, suggesting that AKI impaired the expressions of OAT3, synaptophysin and MAP2 in the brain via IS-induced TNFα release from macrophages or microglia (termed as IS-TNFα axis). Treatment of mice with TNFα (0.5 mg·kg-1·d-1, i.p. for 3 days) significantly increased p-p65 expression and reduced the expressions of Nrf2 and HO-1. Inhibiting NF-κB pathway, silencing p65, or activating Nrf2 and HO-1 obviously attenuated TNFα-induced downregulation of OAT3, synaptophysin and MAP2 expressions. Significantly increased p-p65 and decreased Nrf2 and HO-1 protein levels were also detected in brain of AKI mice and rats. We conclude that AKI inhibits the expressions of OAT3, synaptophysin and MAP2 due to IS-induced TNFα release from macrophages or microglia. TNFα impairs the expressions of OAT3, synaptophysin and MAP2 partly via activating NF-κB pathway and inhibiting Nrf2-HO-1 pathway.

Radiomics analysis for the prediction of locoregional recurrence of locally advanced oropharyngeal cancer and hypopharyngeal cancer.

PURPOSE: By radiomic analysis of the postcontrast CT images, this study aimed to predict locoregional recurrence (LR) of locally advanced oropharyngeal cancer (OPC) and hypopharyngeal cancer (HPC). METHODS: A total of 192 patients with stage III-IV OPC or HPC from two independent cohort were randomly split into a training cohort with 153 cases and a testing cohort with 39 cases. Only primary tumor mass was manually segmented. Radiomic features were extracted using PyRadiomics, and then the support vector machine was used to build the radiomic model with fivefold cross-validation process in the training data set. For each case, a radiomics score was generated to indicate the probability of LR. RESULTS: There were 94 patients with LR assigned in the progression group and 98 patients without LR assigned in the stable group. There was no significant difference of TNM staging, treatment strategies and common risk factors between these two groups. For the training data set, the radiomics model to predict LR showed 83.7% accuracy and 0.832 (95% CI 0.72, 0.87) area under the ROC curve (AUC). For the test data set, the accuracy and AUC slightly declined to 79.5% and 0.770 (95% CI 0.64, 0.80), respectively. The sensitivity/specificity of training and test data set for LR prediction were 77.6%/89.6%, and 66.7%/90.5%, respectively. CONCLUSIONS: The image-based radiomic approach could provide a reliable LR prediction model in locally advanced OPC and HPC. Early identification of those prone to post-treatment recurrence would be helpful for appropriate adjustments to treatment strategies and post-treatment surveillance.

Canonical correlation analysis on the association between HIV-related stress and health-related quality of life among newly diagnosed people living with HIV.

The overall negative correlation between HIV-related stress and health related quality of life (HRQoL) among people living with HIV (PLWH) has been established, but less is known about the associations between them from various dimensions. We aimed to give a deep understanding of the relationship between these two multidimensional variables. A cross-sectional study of 557 PLWH with diagnosis less than 1 month was conducted. The HIV/AIDS Stress Scale (SS-HIV) and the Medical Outcomes Study HIV Survey (MOS-HIV) were used to assess the HIV-related stress and HRQoL, respectively. Canonical correlation analysis was performed to analyze their correlation. The association between HIV-related stress and HRQoL among PLWH was mainly determined by the emotional stress and four HRQoL dimensions including health transition, heath stress, mental health function and the attitude towards general quality of life, which should be taken as important considerations in the management of HIV.

Prediction of poor outcome in stroke patients using radiomics analysis of intraparenchymal and intraventricular hemorrhage and clinical factors.

PURPOSE: To build three prognostic models using radiomics analysis of the hemorrhagic lesions, clinical variables, and their combination, to predict the outcome of stroke patients with spontaneous intracerebral hemorrhage (sICH). MATERIALS AND METHODS: Eighty-three sICH patients were included. Among them, 40 patients (48.2%) had poor prognosis with modified Rankin scale (mRS) of 5 and 6 at discharge, and the prognostic model was built to differentiate mRS ≤ 4 vs. 5 + 6. The region of interest (ROI) of intraparenchymal hemorrhage (IPH) and intraventricular hemorrhage (IVH) were separately segmented. Features were extracted using PyRadiomics, and the support vector machine was applied to select features and build radiomics models based on IPH and IPH + IVH. The clinical models were built using multivariate logistic regression, and then the radiomics scores were combined with clinical variables to build the combined model. RESULTS: When using IPH, the AUC for radiomics, clinical, and combined model was 0.78, 0.82, and 0.87, respectively. When using IPH + IVH, the AUC was increased to 0.80, 0.84, and 0.90, respectively. The combined model had a significantly improved AUC compared to the radiomics by DeLong test. A clinical prognostic model based on the ICH score of 0-1 only achieved AUC of 0.71. CONCLUSIONS: The combined model using the radiomics score derived from IPH + IVH and the clinical factors could achieve a high accuracy in prediction of sICH patients with poor outcome, which may be used to assist in making the decision about the optimal care.

Daily mood and cognitive performance of women with and without bipolar disorder: role of menopausal status.

We examined the role of menopausal status in daily mood and cognitive performance among women with bipolar disorder (BD) compared to healthy comparison women. We analyzed the association of menopausal status, bipolar diagnosis, and their interaction on daily mood assessed by mobile surveys and attentional performance measured multiple times over 2 weeks. Menopausal status was associated with more daily negative affect in women with BD, but not related to attentional performance.

Construction and validation of a nomogram for HBV-related hepatocellular carcinoma: A large, multicenter study.

INTRODUCTION AND OBJECTIVES: We initiated this multicenter study to integrate important risk factors to create a nomogram for hepatitis B virus (HBV)-related hepatocellular carcinoma (HCC) for clinician decision-making. PATIENTS AND METHODS: Between April 2011 and March 2022, 2281 HCC patients with an HBV-related diagnosis were included. All patients were randomly divided into two groups in a ratio of 7:3 (training cohort, n = 1597; validation cohort, n = 684). The nomogram was built in the training cohort via Cox regression model and validated in the validation cohort. RESULTS: Multivariate Cox analyses revealed that the portal vein tumor thrombus, Child-Pugh class, tumor diameter, alanine aminotransferase level, tumor number, extrahepatic metastases, and therapy were independent predictive variables impacting overall survival. We constructed a new nomogram to predict 1-, 2-, and 3-year survival rates based on these factors. The nomogram-related receiver operating characteristics (ROC) curves indicated that the area under the curve (AUC) values were 0.809, 0.806, and 0.764 in predicting 1-, 2-, and 3-year survival rates, respectively. Furthermore, the calibration curves revealed good agreement between real measurements and nomogram predictions. The decision curve analyses (DCA) curves demonstrated excellent therapeutic application potential. In addition, stratified by risk scores, low-risk groups had longer median OS than medium-high-risk groups (p < 0.001). CONCLUSIONS: The nomogram we constructed showed good performance in predicting the 1-year survival rate for HBV- related HCC.

Nb2O5 Coating to Improve the Cyclic Stability and Voltage Decay of Li-Rich Cathode Material for Lithium-Ion Battery.

The commercialization of lithium manganese oxide (LMO) is seriously hindered by several drawbacks, such as low initial Coulombic efficiency, the degradation of the voltage and capacity during cycling, and the poor rating performance. Developing a simple and scalable synthesis for engineering with surface coating layers is significant and challenging for the commercial prospects of LMO oxides. Herein, we have proposed an efficient engineering strategy with a Nb2O5 coating layer. We dissolved niobate (V) ammonium oxalate hydrate and stoichiometric rich LMO (RLM) in deionized water and stirred constantly. Then, the target product was calcined at high temperature. The discharge capacity of the Nb2O5 coating RLM is increased from 195 mAh·g-1 (the RLM without Nb2O5) to 215 mAh·g-1 at a coating volume ratio of 0.010. The average voltage decay was 4.38 mV/cycle, which was far lower than the 7.50 mV/cycle for the pure LMO. The electrochemical kinetics results indicated that the performance was superior with the buffer engineering by the Nb2O5 coating of RLM, which provided an excellent lithium-ion conduction channel, and improved diffusion kinetics, capacity fading, and voltage decay. This reveals the strong potential of the Nb2O5 coating in the field of cathode materials for lithium-ion batteries.

Stimuli-Responsive Pickering Emulsions Regulated via Polymerization-Induced Self-Assembly Nanoparticles.

With the development of reversible deactivated radical polymerization techniques, polymerization-induced self-assembly (PISA) is emerging as a facile method to prepare block copolymer nanoparticles in situ with high concentrations, providing wide potential applications in different fields, including nanomedicine, coatings, nanomanufacture, and Pickering emulsions. Polymeric emulsifiers synthesized by PISA have many advantages comparing with conventional nanoparticle emulsifiers. The morphologies, size, and amphiphilicity can be readily regulated via the synthetic process, post-modification, and external stimuli. By introducing stimulus responsiveness into PISA nanoparticles, Pickering emulsions stabilized with these nanoparticles can be endowed with "smart" behaviors. The emulsions can be regulated in reversible emulsification and demulsification. In this review, the authors focus on recent progress on Pickering emulsions stabilized by PISA nanoparticles with stimuli-responsiveness. The factors affecting the stability of emulsions during emulsification and demulsification are discussed in details. Furthermore, some viewpoints for preparing stimuli-responsive emulsions and their applications in antibacterial agents, diphase reaction platforms, and multi-emulsions are discussed as well. Finally, the future developments and applications of stimuli-responsive Pickering emulsions stabilized by PISA nanoparticles are highlighted.

Crystallizable Aliphatic Chains Enhanced Covalent Adaptable Networks: Fast Reprocessing and Improved Performance.

Covalent adaptable networks (CANs) exhibit recyclability such as reprocessing, but it's a challenge to address the contradiction between reprocessing rate and performance. Here, pendent aliphatic chain anhydride monoesters are innovatively introduced into epoxy CANs based on transesterification, which efficiently accelerates the reprocessing without sacrificing thermal and mechanical properties. The transesterification rate is raised on account of the flexible aliphatic chain-promoted segment movement and dynamic transfer auto-catalysis. When the carbon number reflecting the length of the pendent chain is 12, the epoxy CAN exhibits the fastest stress relaxation or reprocessing. Computation via molecular dynamics simulation demonstrates that the increased segmental mobility from the pendent aliphatic chains contributes to enhanced reprocessability. Interestingly, the crystallization of the pendent aliphatic chains maintains or even improves the thermal and mechanical properties. Thus, introducing a flexible and crystallizable aliphatic side chain is an innovative and efficient approach to accelerate dynamic reactions and network arrangement while improving performance.

Fast-Reprocessing, Postadjustable, Self-Healing Covalent Adaptable Networks with Schiff Base and Diels-Alder Adduct.

Covalent adaptable networks (CANs) are a new type of polymers, which possess excellent performance of thermosets and reprocessability of thermoplastics. Nevertheless, it is still a challenge to realize rapid reprocessing and postadjusting (adjust properties after preparation). Herein, for the first time, a method of combining Schiff base and Diels-Alder adduct in one network is developed to achieve rapid reprocessing and postadjusting. Through the dissociation of the Diels-Alder adduct at high temperatures, the cross-link densities of the networks are reduced, thereby accelerating the rearrangement of the networks and realizing the rapid reprocessing and self-healing. Moreover, the reconnecting degree of network after dissociation of Diels-Alder adduct can be easily controlled by annealing; as a result, the properties of the obtained CANs are postadjustable. This work provides a simple and promising approach of achieving excellent reprocessing and postadjusting for CANs via the synergism of an associative dynamic chemistry with a dissociative dynamic chemistry.

Bacteria-driven hypoxia targeting delivery of chemotherapeutic drug proving outcome of breast cancer.

Local hypoxia is a common feature of many solid tumors and may lead to unsatisfactory chemotherapy outcomes. Anaerobic bacteria that have an affinity to hypoxic areas can be used to achieve targeted drug delivery in tumor tissues. In this study, we developed a biocompatible bacteria/nanoparticles biohybrid (Bif@DOX-NPs) platform that employs the anaerobic Bifidobacterium infantis (Bif) to deliver adriamycin-loaded bovine serum albumin nanoparticles (DOX-NPs) into breast tumors. The Bif@DOX-NPs retained the targeting ability of B. infantis to hypoxic regions, as well as the cytotoxicity of DOX. The biohybrids were able to actively colonize the hypoxic tumors and significantly increased drug accumulation at the tumor site. The DOX concentration in the tumor masses colonized by Bif@DOX-NPs was 4 times higher than that in the free DOX-treated tumors, which significantly prolonged the median survival of the tumor-bearing mice to 69 days and reduced the toxic side-effects of DOX. Thus, anaerobic bacteria-based biohybrids are a highly promising tool for the targeted treatment of solid tumors with inaccessible hypoxic regions.

Endometrial microstimulation effects on endometrial receptivity assessed by transvaginal color Doppler sonography.

OBJECTIVE: This study investigated the effect of endometrial microstimulation (EM) on endometrial receptivity using transvaginal color Doppler sonography (TVCDS). METHOD: Women of childbearing age who were preparing to conceive (n = 90) were randomly divided into the EM group (n = 30), who were examined by EM on days 3-5 of the menstrual cycle, and the control group (n = 60). TVCDS was conducted during the implantation window phase, and endometrial thickness, endometrial pattern, endometrial movement, blood flow type, and uterine and spiral arterial hemodynamic parameter measurements were made. The groups were compared to identify differences. RESULTS: Endometrial thickness (0.97 ± 0.18 cm and 0.95 ± 0.17 cm), endometrial movement (type 1: 46.7% and 51.7%; type 2: 30.0% and 28.3%; type 3: 6.7% and 5.0%; type 5: 16.7% and 15.0%), and hemodynamic parameters of the uterine (pulsatility index [PI]: 2.46 ± 0.50 and 2.41 ± 0.48; resistance index [RI]: 0.85 ± 0.05 and 0.84 ± 0.05) and spiral (PI: 1.11 ± 0.32 and 1.19 ± 0.33; RI: 0.48 ± 0.11 and 0.51 ± 0.08) arteries did not differ significantly between groups (P > 0.05). However, the endometrial pattern (a trilaminar pattern: 80.0% and 58.3%; P = 0.041) and blood flow type (type I: 16.7% and 43.3%; type II: 63.3% and 40.0%; type III 20.0% and 16.7%; P = 0.038) differed significantly between groups. CONCLUSION: Endometrial microstimulation did not alter endometrial pathological staging, endometrial thickness, or movement, nor did it affect uterine and spiral arterial blood flow parameters. However, it may be able to abrade abnormal endometrial tissue, optimizing the endometrial pattern. Endometrial microstimulation may support local spiral artery regeneration and increase endometrial blood supply in new cycles.

A deep learning-based method for the diagnosis of vertebral fractures on spine MRI: retrospective training and validation of ResNet.

PURPOSE: To improve the performance of less experienced clinicians in the diagnosis of benign and malignant spinal fracture on MRI, we applied the ResNet50 algorithm to develop a decision support system. METHODS: A total of 190 patients, 50 with malignant and 140 with benign fractures, were studied. The visual diagnosis was made by one senior MSK radiologist, one fourth-year resident, and one first-year resident. The MSK radiologist also gave the binary score for 15 qualitative imaging features. Deep learning was implemented using ResNet50, using one abnormal spinal segment selected from each patient as input. The T1W and T2W images of the lesion slice and its two neighboring slices were considered. The diagnostic performance was evaluated using tenfold cross-validation. RESULTS: The overall reading accuracy was 98, 96, and 66% for the senior MSK radiologist, fourth-year resident, and first-year resident, respectively. Of the 15 imaging features, 10 showed a significant difference between benign and malignant groups with p < = 0.001. The accuracy achieved by using the ResNet50 deep learning model for the identified abnormal vertebral segment was 92%. Compared to the first-year resident's reading, the model improved the sensitivity from 78 to 94% (p < 0.001) and the specificity from 61 to 91% (p < 0.001). CONCLUSION: Our deep learning-based model may provide information to assist less experienced clinicians in the diagnosis of spinal fractures on MRI. Other findings away from the vertebral body need to be considered to improve the model, and further investigation is required to generalize our findings to real-world settings.

Application of comprehensive pharmaceutical care program in identifying and addressing drug-related problems in hospitalized patients with osteoporosis.

BACKGROUND: More information about the impacts of comprehensive pharmaceutical care program (CPCP) on the identification and resolution of drug-related problems (DRPs) is needed. This study aimed at researching the characteristics of DRPs in osteoporosis patients and evaluating the effect of CPCP in identifying and addressing DRPs. METHODS: We performed a prospective interventional study in a teaching hospital. CPCP was established and conducted to identify and resolve DRPs by a multidisciplinary team (MDT) based on the Pharmaceutical Care Network Europe (PCNE) classification V9.0. Six pharmacists and one doctor worked directly in the study. All data was obtained from electronic medical records, direct observation and visits. The statistical analyses were performed using the SPSS Statistics software version 26.0. RESULTS: Two hundred nineteen patients with osteoporosis were included in the final analysis. A total of 343 DRPs were identified, with an average of 1.57 DRPs per patient. The most common DRPs identified were "treatment safety P2" (66.8%; 229/343), followed by "other P3" (21.0%; 72/343) and "treatment effectiveness, P1" (12.2%; 42/343). The primary causes of DRPs were "dose selection C3" (35.9%; 211/588), followed by "drug use process C6" (28.9%; 170/588) and "drug selection C1" (12.6%; 74/588). Seven hundred eleven interventions were proposed to address the 343 DRPs, with an average of 2.1 interventions per DRP. The acceptance rate reached 95.9, and 91.0% of these accepted interventions were fully implemented. As a result, only 30 DRPs were unsolved before discharge. Additionally, the number of drugs was found to be associated with the number of DRPs significantly (p = 0.023). CONCLUSION: DRPs frequently occurred in hospitalized osteoporosis patients. CPCP could be an effect option to solve and reduce DRPs for osteoporosis patients and should be implemented widely to increase patient safety.

Impact of serine and serine synthesis genes on H2S release in Saccharomyces cerevisiae during wine fermentation.

Excessive hydrogen sulfide (H2S) during fermentation causes undesirable sensory properties in wine. In yeast, serine functions as a precursor in the biosynthesis of S-containing compounds, which facilitates H2S consumption. To investigate the effect of serine on H2S release and the underlying mechanism, extracellular and intracellular serine levels were separately increased under fermentation conditions. The results show that, although the abundance of extracellular serine was ineffective in decreasing H2S levels, increased levels of intracellular serine levels from SER1 and SER2 overexpression reduced H2S release through increased consumption of sulfur metabolites. In contrast, SER33 overexpression significantly increased H2S release, and the metabolites and gene expression profile of the sulfur assimilation pathway indicates that SER33 regulated MET17, which mediated H2S release. Our study revealed valuable insights on the relationship between serine levels and H2S release, and may be helpful in understanding the H2S regulation mechanism in yeast during fermentation.