Fugacity- and biotransformation-based mechanistic insights into the trophic transfer of organophosphate flame retardants in a subtropical coastal food web from the Northern Beibu Gulf of China.

The bioaccumulation and trophic transfer of organophosphate flame retardants (OPFRs) in marine ecosystems have attracted great attention in recent research, but our understanding of the trophic transfer mechanisms involved is limited. In this study, we investigated the trophodynamics of OPFRs and their metabolites in a subtropical coastal food web collected from the northern Beibu Gulf, China, and characterized their trophodynamics using fugacity- and biotransformation-based approaches. Eleven OPFRs and all seven metabolites were simultaneously quantified in the shellfish, crustacean, pelagic fish, and benthic fish samples, with total concentrations ranging from 164 to 4.11 × 104 and 4.56-4.28 × 103 ng/g lipid weight, respectively. Significant biomagnification was observed only for tris (phenyl) phosphate (TPHP) and tris (2-ethylhexyl) phosphate (TEHP), while other compounds except for tris(2-chloroethyl) phosphate (TCEP) displayed biomagnification trends based on Monte Carlo simulations. Using a fugacity-based approach to normalize the accumulation of OPFRs in biota to their relative biological phase composition, storage lipid is the predominant biological phase for the mass distribution of 2-ethylhexyl diphenyl phosphate (EHDPHP) and TPHP. The water content and structure protein are equally important for TCEP, whereas lipid and structure protein are the two most important phases for other OPFRs. The mass distribution of these OPFRs along with TLs can explain their trophodynamics in the food web. The organophosphate diesters (as OPFR metabolites) also displayed biomagnification trends based on bootstrapped estimation. The correlation analysis and Korganism-water results jointly suggested the metabolites accumulation in high-TL organisms was related to biotransformation processes. The metabolite-backtracked trophic magnification factors for tri-n­butyl phosphate (TNBP) and TPHP were both greater than the values that accounted for only the parent compounds. This study highlights the incorporation of fugacity and biotransformation analysis to characterize the trophodynamic processes of OPFRs and other emerging pollutants in food webs.

Predicting High-Risk Esophageal Varices in Cirrhosis: A Multi-Parameter Splenic CT Study.

RATIONALE AND OBJECTIVES: To explore the value of splenic hemodynamic parameters from low-dose one-stop dual-energy and perfusion CT (LD-DE&PCT) in non-invasively predicting high-risk esophageal varices (HREV) in cirrhotic patients. METHODS: We retrospectively analyzed cirrhotic patients diagnosed with esophageal varices (EV) through clinical, laboratory, imaging, and endoscopic examinations from September 2021 to December 2023 in our hospital. All patients underwent LD-DE&PCT to acquire splenic iodine concentration and perfusion parameters. Radiation dose was recorded. Patients were classified into non-HREV and HREV groups based on endoscopy. Univariate and multivariate logistic regression analysis were performed, and the prediction model for HREV was constructed. P < 0.05 was considered statistically significant. RESULTS: Univariate analysis revealed that significant differences were found in portal iodine concentration (PIC), blood flow (BF), permeability surface (PS), spleen volume (V-S), total iodine concentration (TIC), and total blood volume of the spleen (BV-S) between groups. TIC demonstrated the highest predictive value with an area under the curve (AUC) value of 0.87. Multivariate analysis showed that PIC, PS, and BV-S were independent risk factors for HREV. The logistic regression model for predicting HREV had an AUC of 0.93. The total radiation dose was 20.66 ± 4.07 mSv. CONCLUSION: Splenic hemodynamic parameters obtained from LD-DE&PCT can non-invasively and accurately assess the hemodynamic status of the spleen in cirrhotic patients with EV and predict the occurrence of HREV. Despite the retrospective study design and limited sample size of this study, these findings deserve further validation through prospective studies with larger cohorts.

Complex heterozygous mutations in hereditary spherocytosis: A case report.

BACKGROUND: The aim of this study was to investigate the complex heterozygous mutations of ANK1 and SPTA1 in the same individual and improve our understanding of hereditary spherocytosis (HS) in children. We also hope to promote the application of gene detection technology in children with HS, with the goals of identifying more related gene mutations, supporting the acquisition of improved molecular genetic information to further reveal the pathogenesis of HS in children, and providing important guidance for the diagnosis, treatment, and prevention of HS in children. CASE SUMMARY: A 1-year and 5-month-old patient presented jaundice during the neonatal period, mild anemia 8 months later, splenic enlargement at 1 year and 5 months, and brittle red blood cell permeability. Genetic testing was performed on the patient, their parents, and sister. Swiss Model software was used to predict the protein structure of complex heterozygous mutations in ANK1 and SPTA1. Genetic testing revealed that the patient harbored a new mutation in the ANK1 gene from the father and a mutation in the SPTA1 gene from the mother. Combined with the clinical symptoms of the children, it is suggested that the newly discovered complex heterozygous mutations of ANK1 and SPTA1 may be the cause, providing important guidance for revealing the pathogenesis, diagnosis, treatment, and promotion of gene detection technology in children with HS. CONCLUSION: This case involves an unreported complex heterozygous mutation of ANK1 and SPTA1, which provides a reference for exploring HS.

Exploring drug repositioning possibilities of kinase inhibitors via molecular simulation.

Kinases, a class of enzymes controlling various substrates phosphorylation, are pivotal in both physiological and pathological processes. Although their conserved ATP binding pockets pose challenges for achieving selectivity, this feature offers opportunities for drug repositioning of kinase inhibitors (KIs). This study presents a cost-effective in silico prediction of KIs drug repositioning via analyzing cross-docking results. We established the KIs database (278 unique KIs, 1834 bioactivity data points) and kinases database (357 kinase structures categorized by the DFG motif) for carrying out cross-docking. Comparative analysis of the docking scores and reported experimental bioactivity revealed that the Atypical, TK, and TKL superfamilies are suitable for drug repositioning. Among these kinase superfamilies, Olverematinib, Lapatinib, and Abemaciclib displayed enzymatic activity in our focused AKT-PI3K-mTOR pathway with IC50 values of 3.3, 3.2 and 5.8 µM. Further cell assays showed IC50 values of 0.2, 1.2 and 0.6 µM in tumor cells. The consistent result between prediction and validation demonstrated that repositioning KIs via in silico method is feasible.

Correlation between clinical characteristics and epicardial adipose tissue features in acute myocarditis patients using coronary computed tomography (CT) vascular imaging: a case-control study with retrospective data collection.

Background: Epicardial adipose tissue (EAT) is unique type of visceral adipose tissue, sharing the same microcirculation with myocardium. This study aimed to assess the imaging features of EAT in patients with acute myocarditis (AM) and explore the relationships with clinical characteristics. Methods: For this retrospective case-control study, totally 38 AM patients and 52 controls were screened retrospectively from January 2019 to December 2022, and the EAT volume was measured from coronary computed tomography (CT) angiography imaging. Histogram analysis was performed to calculate parameters like the mean, standard deviation, interquartile range and percentiles of EAT attenuation. Whether EAT features change was assessed when clinical characteristics including symptoms, T wave abnormalities, pericardial effusion (PE), impairment of systolic function, and the need for intensive care presented. Results: The EAT volume (75.2±22.8 mL) and mean EAT attenuation [-75.8±4.4 Hounsfield units (HU)] of the AM group was significantly larger than the control group (64.7±26.0 mL, P=0.049; -77.9±5.0 HU, P=0.044). Among the clinical characteristics, only the presence of PE was associated with changes in EAT features. Patients with PE showed significantly changes in EAT attenuation including mean attenuation [analysis of variance (ANOVA) P=0.001] and quantitative histogram parameters. The mean attenuation of patients with PE (-71.9±4.0 HU) was significantly larger than controls (-77.9±5.0 HU, Bonferroni corrected P<0.001) and patients without PE (-77.4±3.5 HU, Bonferroni corrected P=0.003). Observed in histogram, the overall increase in EAT attenuation could lead to decrease in EAT volume, which resulted in no statistically significant difference in EAT volume between the AM patients with PE and controls (64.7±26.0 vs. 72.2±28.3 mL, Bonferroni corrected P>0.99). Conclusions: Compared to controls, EAT volume was significantly larger in AM, and EAT attenuation increased notably in the presence of PE. We recommend evaluating EAT volume and attenuation simultaneously when quantifying EAT using CT attenuation thresholds.

Pleural carbohydrate antigen 50 and malignant pleural effusion: a prospective, double-blind diagnostic accuracy test.

Background: Serum carbohydrate antigen 50 (CA50) is an auxiliary diagnostic marker for various solid tumors, but it remains unclear whether CA50 in pleural fluid can assist in the diagnosis of malignant pleural effusion (MPE). This study aimed to evaluate the diagnostic accuracy of pleural fluid CA50 for MPE in pleural effusion patients with undetermined causes. Methods: This study prospectively recruited pleural effusion patients with undetermined causes who visited the Affiliated Hospital of Inner Mongolia Medical University between September 2018 and July 2021. We measured pleural fluid CA50 level with an electrochemiluminescence assay. We analyzed the diagnostic accuracy of CA50 and carcinoembryonic antigen (CEA) for MPE with the receiver operating characteristic (ROC) curve. The net benefits of CA50 and CEA were analyzed using the decision curve analysis (DCA). Results: We enrolled 66 MPEs and 87 benign pleural effusions (BPEs). MPE patients had significantly higher CA50 and CEA than BPE patients. The area under the ROC curve (AUC) of CA50 was 0.72 (95% CI: 0.63-0.80). CA50 had a sensitivity of 0.30 (95% CI: 0.19-0.41) and a specificity of 1.00 (95% CI: 1.00-1.00) at the threshold of 15 IU/mL. The decision curve of CA50 was above the reference line at the calculated risk probability of between 0.30 and 1.00. Venn diagram indicated that some patients with low CEA (<50 or <150 ng/mL) and/or negative cytology can be identified by positive CA50 (>15 IU/mL). Conclusions: Pleural fluid CA50 has moderate accuracy and net benefit for detecting MPE. CA50 >15 IU/mL can be used to diagnose MPE. The combination of CA50 and CEA improves the diagnostic sensitivity for MPE.

FDAA: A feature distribution-aware transferable adversarial attack method.

In recent years, the research on transferable feature-level adversarial attack has become a hot spot due to attacking unknown deep neural networks successfully. But the following problems limit its transferability. Existing feature disruption methods often focus on computing feature weights precisely, while overlooking the noise influence of feature maps, which results in disturbing non-critical features. Meanwhile, geometric augmentation algorithms are used to enhance image diversity but compromise information integrity, which hamper models from capturing comprehensive features. Furthermore, current feature perturbation could not pay attention to the density distribution of object-relevant key features, which mainly concentrate in salient region and fewer in the most distributed background region, and get limited transferability. To tackle these challenges, a feature distribution-aware transferable adversarial attack method, called FDAA, is proposed to implement distinct strategies for different image regions in the paper. A novel Aggregated Feature Map Attack (AFMA) is presented to significantly denoise feature maps, and an input transformation strategy, called Smixup, is introduced to help feature disruption algorithms to capture comprehensive features. Extensive experiments demonstrate that scheme proposed achieves better transferability with an average success rate of 78.6% on adversarially trained models.

A novel cascade catalysis for one-pot enzymatically modified isoquercitrin (EMIQ) conversion from rutin and sucrose using rationally designed gradient temperature control.

Enzymatically modified isoquercitrin (EMIQ) is a glyco-chemically modified flavonoid exhibiting notably high biological activity, such as antioxidant, anti-inflammatory and anti-allergic properties. However, the utilization of expensive substrates such as isoquercitrin and cyclodextrin in the conventional approach has hindered the industrial-scale production of EMIQ due to high cost and low yields. Hence, the development of a cost-effective and efficient method is crucial for the biological synthesis of EMIQ. In this study, a natural cascade catalytic reaction system was constructed with α-L-rhamnosidase and amylosucrase using the inexpensive substrates rutin and sucrose. Additionally, a novel approach integrating gradient temperature regulation into biological cascade reactions was implemented. Under the optimal conditions, the rutin conversion reached a remarkable 95.39% at 24 h. Meanwhile, the productivity of quercetin-3-O-tetraglucoside with the best bioavailability reached an impressive 41.69%. This study presents promising prospects for future mass production of EMIQ directly prepared from rutin and sucrose.

PGCNMDA: Learning node representations along paths with graph convolutional network for predicting miRNA-disease associations.

Identifying miRNA-disease associations (MDAs) is crucial for improving the diagnosis and treatment of various diseases. However, biological experiments can be time-consuming and expensive. To overcome these challenges, computational approaches have been developed, with Graph Convolutional Network (GCN) showing promising results in MDA prediction. The success of GCN-based methods relies on learning a meaningful spatial operator to extract effective node feature representations. To enhance the inference of MDAs, we propose a novel method called PGCNMDA, which employs graph convolutional networks with a learning graph spatial operator from paths. This approach enables the generation of meaningful spatial convolutions from paths in GCN, leading to improved prediction performance. On HMDD v2.0, PGCNMDA obtains a mean AUC of 0.9229 and an AUPRC of 0.9206 under 5-fold cross-validation (5-CV), and a mean AUC of 0.9235 and an AUPRC of 0.9212 under 10-fold cross-validation (10-CV), respectively. Additionally, the AUC of PGCNMDA also reaches 0.9238 under global leave-one-out cross-validation (GLOOCV). On HMDD v3.2, PGCNMDA obtains a mean AUC of 0.9413 and an AUPRC of 0.9417 under 5-CV, and a mean AUC of 0.9419 and an AUPRC of 0.9425 under 10-CV, respectively. Furthermore, the AUC of PGCNMDA also reaches 0.9415 under GLOOCV. The results show that PGCNMDA is superior to other compared methods. In addition, the case studies on pancreatic neoplasms, thyroid neoplasms and leukemia show that 50, 50 and 48 of the top 50 predicted miRNAs linked to these diseases are confirmed, respectively. It further validates the effectiveness and feasibility of PGCNMDA in practical applications.

Measuring the Boundary Gapless State and Criticality via Disorder Operator.

The disorder operator is often designed to reveal the conformal field theory (CFT) information in quantum many-body systems. By using large-scale quantum Monte Carlo simulation, we study the scaling behavior of disorder operators on the boundary in the two-dimensional Heisenberg model on the square-octagon lattice with gapless topological edge state. In the Affleck-Kennedy-Lieb-Tasaki phase, the disorder operator is shown to hold the perimeter scaling with a logarithmic term associated with the Luttinger liquid parameter K. This effective Luttinger liquid parameter K reflects the low-energy physics and CFT for (1+1)D boundary. At bulk critical point, the effective K is suppressed but it keeps finite value, indicating the coupling between the gapless edge state and bulk fluctuation. The logarithmic term numerically captures this coupling picture, which reveals the (1+1)D SU(2)_{1} CFT and (2+1)D O(3) CFT at boundary criticality. Our Letter paves a new way to study the exotic boundary state and boundary criticality.

Chronic inflammatory demyelinating polyneuropathy with pulmonary nocardiosis: A case report.

RATIONALE: Chronic inflammatory demyelinating polyneuropathy (CIDP) is an immune-mediated motor sensory peripheral neuropathy that is rare in clinical practice. This treatment method aims to suppress potential immunopathology. Nocardiosis is a rare, destructive, opportunistic disease. We report a case of failed treatment of CIDP combined with pulmonary nocardiosis, and for the first time, we link these 2 diseases together. PATIENT CONCERNS: A 65-year-old man developed symmetrical limb weakness. Four months later, he was diagnosed with CIDP and started receiving glucocorticoid (GC) treatment. The disease progressed slowly and was treated with mycophenolate mofetil (MMF) in combination. He did not follow the doctor requirements for monthly follow-up visits, and the preventive medication for sulfamethoxazole/trimethoprim was not strictly implemented. Two months after the combination therapy, the patient developed fever, coughing and sputum production, as well as fatigue and poor appetite. Based on imaging and etiological results, he was diagnosed with pulmonary nocardiosis. DIAGNOSES: Chronic inflammatory demyelinating polyneuropathy, pulmonary nocardiosis. INTERVENTIONS: After treatment with antibiotics, the patient lung infection temporarily improved. However, the patient CIDP condition progressed, limb weakness worsened, respiratory muscle involvement occurred, and intravenous immunoglobulin (IVIG) was administered. However, there was no significant improvement in the condition, and the patient died. OUTCOMES: In this report, we present a case of a patient with CIDP and pulmonary nocardiosis. It is worth noting that in order to avoid the progression and recurrence of CIDP, we did not stop using related therapeutic drugs during the treatment process, the patient had repeatedly refused to use IVIG. Despite this, the patient condition worsened when lung inflammation improved, leading to persistent respiratory failure and ultimately death. Treatment contradictions, medication issues, and patient compliance issues reflected in this case are worth considering. LESSONS: For patients with CIDP receiving immunosuppressive therapy, attention should be paid to the occurrence and severity of Nocardia infection. Therefore, early detection and treatment are necessary. We need to pay attention to the compliance of patients with prophylactic use of antibiotics, strengthen the follow-up, and urge them to return to their appointments on time.

Improved Mobility-Stretchability Properties of Diketopyrrolopyrrole-Based Conjugated Polymers with Diastereomeric Conjugation Break Spacers.

Stretchable conjugated polymers with conjugation break spacers (CBSs) synthesized via random terpolymerization have gained considerable attention because of their efficacy in modulating mobility and stretchability. This study incorporates a series of dianhydrohexitol diastereomers of isosorbide (ISB) and isomannide (IMN) units into the diketopyrrolopyrrole-based backbone as CBSs. It is found that the distorted CBS (IMN) improves the mobility-stretchability properties of the polymer with a highly coplanar backbone, whereas the extended CBS (ISB) enhances those of the polymer with a noncoplanar backbone. Additionally, the different configurations of ISB and IMN sufficiently affect the solid-state packing, aggregation capabilities, crystallographic parameters, and mobility-stretchability properties of the polymer. The IMN-based polymers exhibit the highest mobility of 1.69 cm2 V-1 s-1 and crystallinity retentions of (85.7, 78.6)% under 20% and 60% strains, outperforming their ISB-based or unmodified counterparts. The improvement is correlated with a robust aggregation capability. Furthermore, the CBS content affects aggregation behavior, notably affecting mobility. This result indicates that incorporating CBSs into the polymer can enhance backbone flexibility via movement and rotation of the CBS without affecting the crystalline regions.

Electron Spin Broken-Symmetry of Fe-Co Diatomic Pairs to Promote Kinetics of Bifunctional Oxygen Electrocatalysis for Zinc-Air Batteries.

Designing bifunctional catalysts to reduce the oxygen evolution reaction (OER) and oxygen reduction reaction (ORR) reaction barriers while accelerating the reaction kinetics is perceived to be a promising strategy to improve the performance of Zinc-air batteries. Unsymmetric configuration in single-atom catalysts has attracted attention due to its unique advantages in regulating electron orbitals. In this work, a seesaw effect in unsymmetric Fe-Co bimetallic monoatomic configurations is proposed, which can effectively improve the OER/ORR bifunctional activity of the catalyst. Compared with the symmetrical model of Fe-Co, a strong charge polarization between Co and Fe atoms in the unsymmetric model is detected, in whom the spin-down electrons around Co atoms are much higher than those spin-up electrons. The seesaw effect occurred between Co atoms and Fe atoms, resulting in a negative shift of the d-band center, which means that the adsorption of oxygen intermediates is weakened and more conducive to their dissociation. The optimized reaction kinetics of the catalyst leads to excellent performance in ZABs, with a peak power density of 215 mW cm-2 and stable cycling for >1300 h and >4000 cycles. Flexible Zinc-air batteries have also gained excellent performance to demonstrate their potential in the field of flexible wearables.

Improving bio-conditioning dewatering performance of food waste anaerobic digestate at low ambient temperatures by heating treatment.

Food waste anaerobic digestate (FWAD) containing high concentrations of contaminants must be purified or recycled. Bio-conditioning dewatering followed by activated sludge process (BDAS) has emerged as a promising technology for treating FWAD. However, the bio-conditioning dewatering as a pivotal step of BDAS is often negatively affected by low ambient temperatures often occurred in winter. This study investigated the role of heating FWAD in improving the bio-conditioning dewatering performance of FWAD. Batch experiments demonstrated that the bio-conditioning dewatering efficiency increased with temperature rise. Notably, due to the low energy consumption, 50°C was considered to be the most appropriate heating treatment temperature, realizing a drastic reduction of specific resistance to filtration (SRF) of bio-conditioned FWAD from initial 1.24 × 1012 m/kg in the control at a ambient temperature of 10°C to 5.42 × 1011 m/kg and a saving of 25% in bio-conditioning reagents cost. The results of the pilot-scale and large-scale experiments revealed that heating treatment made the bio-conditioning dewatering more stable regardless of the fluctuation of ambient temperature in practical engineering. The decrease in the viscosity of bio-conditioned FWAD and the enhancement in microbial fermentation liquor flocculation capacity through heating treatment played pivotal roles in improving the bio-conditioning dewatering performance of FWAD. This work provides a cost-effective strategy to achieve efficient bio-conditioning dewatering at a relatively low ambient temperature, which was helpful in the engineering application of the novel BDAS process in wastewater treatment.

Electrical Double-Layer Transistors Comprising Block Copolymer Electrolytes for Low-Power-Consumption Photodetectors.

Electrical double-layer transistors (EDLTs) have received extensive research attention owing to their exciting advantages of low working voltage, high biocompatibility, and sensitive interfacial properties in ultrasensitive portable sensing applications. Therefore, it is of great interest to reduce photodetectors' operating voltage and power consumption by utilizing photo-EDLT. In this study, a series of block copolymers (BCPs) of poly(4-vinylpyridine)-block-poly(ethylene oxide) (P4VP-b-PEO) with different compositions were applied to formulate polyelectrolyte with indigo carmine salt in EDLT. Accordingly, PEO conduces ion conduction in the BCP electrolyte and enhances the carrier transport capability in the semiconducting channel; P4VP boosts the photocurrent by providing charge-trapping sites during light illumination. In addition, the severe aggregation of PEO is mitigated by forming a BCP structure with P4VP, enhancing the stability and photoresponse of the photo-EDLT. By optimizing the BCP composition, EDLT comprising P4VP16k-b-PEO5k and indigo carmine provides the highest specific detectivity of 2.1 × 107 Jones, along with ultralow power consumptions of 0.59 nW under 450 nm light illumination and 0.32 pW under dark state. The results indicate that photo-EDLT comprising the BCP electrolyte is a practical approach to reducing phototransistors' operating voltage and power consumption.

Development of Light, Strong, and Water-Resistant PVA Composite Aerogels.

A significant weakness of many organic and inorganic aerogels is their poor mechanical behaviour, representing a great impediment to their application. For example, polymer aerogels generally have higher ductility than silica aerogels, but their elastic modulus is considered too low. Herein, we developed extremely low loading (<1 wt%) 2D graphene oxide (GO) nanosheets modified poly (vinyl alcohol) (PVA) aerogels via a facile and environmentally friendly method. The aerogel shows a 9-fold increase in compressional modulus compared to a pure polymer aerogel. With a low density of 0.04 mg/mm3 and a thermal conductivity of only 0.035 W/m·K, it outperforms many commercial insulators and foams. As compared to a pure PVA polymer aerogel, a 170% increase in storage modulus is obtained by adding only 0.6 wt% GO nanosheets. The nanocomposite aerogel demonstrates strong fire resistance, with a 50% increase in burning time and little smoke discharge. After surface modification with 1H,1H,2H,2H-Perfluorodecyltriethoxysilane, the aerogel demonstrates water resistance, which is suitable for outdoor applications in which it would be exposed to precipitation. Our research demonstrates a new pathway for considerable improvement in the performance and application of polymer aerogels.

Genomic prediction within and across maize landrace derived populations using haplotypes.

Genomic prediction (GP) using haplotypes is considered advantageous compared to GP solely reliant on single nucleotide polymorphisms (SNPs), owing to haplotypes' enhanced ability to capture ancestral information and their higher linkage disequilibrium with quantitative trait loci (QTL). Many empirical studies supported the advantages of haplotype-based GP over SNP-based approaches. Nevertheless, the performance of haplotype-based GP can vary significantly depending on multiple factors, including the traits being studied, the genetic structure of the population under investigation, and the particular method employed for haplotype construction. In this study, we compared haplotype and SNP based prediction accuracies in four populations derived from European maize landraces. Populations comprised either doubled haploid lines (DH) derived directly from landraces, or gamete capture lines (GC) derived from crosses of the landraces with an inbred line. For two different landraces, both types of populations were generated, genotyped with 600k SNPs and phenotyped as lines per se for five traits. Our study explores three prediction scenarios: (i) within each of the four populations, (ii) across DH and GC populations from the same landrace, and (iii) across landraces using either DH or GC populations. Three haplotype construction methods were evaluated: 1. fixed-window blocks (FixedHB), 2. LD-based blocks (HaploView), and 3. IBD-based blocks (HaploBlocker). In within population predictions, FixedHB and HaploView methods performed as well as or slightly better than SNPs for all traits. HaploBlocker improved accuracy for certain traits but exhibited inferior performance for others. In prediction across populations, the parameter setting from HaploBlocker which controls the construction of shared haplotypes between populations played a crucial role for obtaining optimal results. When predicting across landraces, accuracies were low for both, SNP and haplotype approaches, but for specific traits substantial improvement was observed with HaploBlocker. This study provides recommendations for optimal haplotype construction and identifies relevant parameters for constructing haplotypes in the context of genomic prediction.

Research strategies of small molecules as chemotherapeutics to overcome multiple myeloma resistance.

Multiple myeloma (MM), a cancer of plasma cells, is the second most common hematological malignancy which is characterized by aberrant plasma cells infiltration in the bone marrow and complex heterogeneous cytogenetic abnormalities. Over the past two decades, novel treatment strategies such as proteasome inhibitors, immunomodulators, and monoclonal antibodies have significantly improved the relative survival rate of MM patients. However, the development of drug resistance results in the majority of MM patients suffering from relapse, limited treatment options and uncontrolled disease progression after relapse. There are urgent needs to develop and explore novel MM treatment strategies to overcome drug resistance and improve efficacy. Here, we review the recent small molecule therapeutic strategies for MM, and introduce potential new targets and corresponding modulators in detail. In addition, this paper also summarizes the progress of multi-target inhibitor therapy and protein degradation technology in the treatment of MM.

Mulberry (Morus alba L.) leaf powder modified the processing of meat alternatives: Principal component analysis from apparent properties to chemical bonds.

For texture control in plant-meat alternatives, the interrelationship between apparent characteristics and chemical bonds in high-fiber formulations remains unclear. The influence of mulberry leaf powder on apparent characteristics and chemical bonds of raw materials, block and strip products at addition amounts of 0.5-25% was analyzed. The results showed that 8% addition significantly increased the chewiness of the block by 98.12%. The strips' texture shows a downward trend, and the processing produced more redness and color difference. Additives promoted the formation of voids, lamellar and filamentous structures, and the strip produced more striped structures. Disulfide bonds significantly increased in the block, and the ß-turn in the secondary structure enhanced by 12.20%. The ß-turn transformed into a ß-sheet in strips. Principal component analysis revealed that the texture improvement was associated with producing disulfide bonds and ß-turn, providing a basis for high-fiber components to improve products' apparent characteristics by chemical bonds.