Effect of α-tocopherol, soybean oil, and glyceryl monostearate oleogel on gel properties and the in-vitro digestion of low-salt silver carp (Hypophthalmichthys molitrix) surimi.

To improve nutritional health, a low-salt (0.5 %) silver carp (Hypophthalmichthys molitrix) surimi gel with α-tocopherol, soybean oil, and glyceryl monostearate oleogel was fabricated and evaluated for textural qualities, lipid oxidation, and in-vitro digestion analysis. Based on the texture profile analysis, gel strength, water holding capacity (WHC), rheological, protein secondary structure, and microstructural examination, 5 % oleogel addition to low-salt surimi exhibited similar physicochemical properties to regular-salt surimi gels. By crosslinking myosin and filling protein network voids, the oleogel increased surimi gel density. Increasing oleogel content improved the physicochemical qualities of heat-induced surimi, causing protein aggregation during digestion and reducing digestibility. The presence of oleogel altered protein secondary structure, reducing α-helix content and increasing ß-sheet and other structures, enhancing WHC and gel strength of low salt surimi. Adding oleogel improved the antioxidant activity of digestive solutions. This study will help understand myosin-oleogel interaction and the development of sustainable and nutritious surimi-based foods.

Repeated Sieving for Prediction Model Building with High-Dimensional Data.

Background: The prediction of patients' outcomes is a key component in personalized medicine. Oftentimes, a prediction model is developed using a large number of candidate predictors, called high-dimensional data, including genomic data, lab tests, electronic health records, etc. Variable selection, also called dimension reduction, is a critical step in developing a prediction model using high-dimensional data. Methods: In this paper, we compare the variable selection and prediction performance of popular machine learning (ML) methods with our proposed method. LASSO is a popular ML method that selects variables by imposing an L1-norm penalty to the likelihood. By this approach, LASSO selects features based on the size of regression estimates, rather than their statistical significance. As a result, LASSO can miss significant features while it is known to over-select features. Elastic net (EN), another popular ML method, tends to select even more features than LASSO since it uses a combination of L1- and L2-norm penalties that is less strict than an L1-norm penalty. Insignificant features included in a fitted prediction model act like white noises, so that the fitted model will lose prediction accuracy. Furthermore, for the future use of a fitted prediction model, we have to collect the data of all the features included in the model, which will cost a lot and possibly lower the accuracy of the data if the number of features is too many. Therefore, we propose an ML method, called repeated sieving, extending the standard regression methods with stepwise variable selection. By selecting features based on their statistical significance, it resolves the over-selection issue with high-dimensional data. Results: Through extensive numerical studies and real data examples, our results show that the repeated sieving method selects far fewer features than LASSO and EN, but has higher prediction accuracy than the existing ML methods. Conclusions: We conclude that our repeated sieving method performs well in both variable selection and prediction, and it saves the cost of future investigation on the selected factors.

DHA dietary intervention caused different hippocampal lipid and protein profile in ApoE-/- and C57BL/6J mice.

BACKGROUND: Changes in protein and lipid levels may occur in the Alzheimer's disease brain, and DHA can have beneficial effects on it. To investigate the impact of DHA dietary intervention on brain protein and lipid profile in ApoE-/- mice and C57 mice. METHOD: Three-month-old ApoE-/- mice and C57 mice were randomly divided into two groups respectively, and fed with control diet and DHA-fortified diet for five months. Cortical TC, HDL-C and LDL-C levels and cholesterol metabolism-related protein expression were measured by ELISA or immunohistochemistry methods. Hippocampus were collected for proteomic and lipidomics analysis by LC-MS/MS and differential proteins and lipid metabolites were screened and further analyzed by GO functional annotation and KEGG pathway enrichment analysis. RESULTS: DHA intervention decreased cortical TC level in both C57 and ApoE-/- mice (P < 0.05), but caused different change of cortical HDL-C, LDL-C level and LDL-C/HDL-C ratio in C57 and ApoE-/- mice (P < 0.05). Discrepant cortical and hippocampal LDLR, ABCG1, Lox1 and SORT1 protein expression was found between C57 and ApoE-/- mice (P < 0.05), and DHA treatment caused different changes of these proteins in C57 and ApoE-/- mice (P < 0.05). Differential hippocampal proteins and lipids profile were found in C57 and ApoE-/- mice before and after DHA treatment, which were mainly involved in vesicular transport and phospholipid metabolic pathways. CONCLUSION: ApoE genetic defect caused abnormal cholesterol metabolism, and affected protein and lipid profile, as well as discrepant response of hippocampal protein and lipids profile in the brain of mice given DHA fortified diet intervention.

Human milk fat substitutes rich in 1,3-dioleoyl-2-palmitoylglycerol and 1-oleoyl-2-palmitoyl-3-linoleoylglycerol simultaneously: Preparation strategy and simulated infant in vitro digestion.

In this study, fractionated palm stearin, oleic acid, and linoleic acid were selected as the base materials to prepare human milk fat substitutes (HMFS) rich in OPO and OPL by enzymatic acidolysis combined with physical blending. Under optimum conditions, contents of OPO, OPL, and sn-2 palmitic acid in the OPO and OPL-rich triacylglycerols (TAGs) were higher than that in commercial OPO-rich TAGs, with values of 37.25%, 28.12%, and 79.44%, respectively. Physical blending the OPO and OPL-rich TAGs (47%), bovine milk fat (18%), sunflower oil (13%), coconut oil (13%), corn oil (8%), and palm oil (1%) can obtain HMFS with a fat composition that like HMF. The fatty acid, sn-2 saturated fatty acid, and TAG contents of HMFS were within the lower and upper limit of HMF. The lipolysis degree of infant formula (IF) with HMFS as fat source is 9.0% higher than that of commercial plant oil-based infant formula (PIF), and 3.4% lower than that of human milk. IF with HMFS as fat source released less saturated free fatty acids and more saturated monoacylglycerols during digestion than that of PIF, which would help improve the IF fat utilization by infants.

Consumption of dietary turmeric promotes fat browning and thermogenesis in association with gut microbiota regulation in high-fat diet-fed mice.

This study was designed to verify the anti-obesity effect of dietary turmeric powder (TP) as a traditional cooking spice and its underlying mechanism. The HFD-fed C57BL/6J mice were supplemented with or without TP (8%) for 12 weeks. The results indicated that the glucolipid metabolism disorder of high-fat diet (HFD)-fed mice was significantly ameliorated through the supplementation of TP. The consumption of TP also induced beige-fat development and brown adipose tissue (BAT)-derived nonshivering thermogenesis in HFD-fed obese mice. 16S rDNA-based microbiota or targeted metabolomics analysis indicated that TP ameliorated the intestinal microbiota dysbiosis and microbial metabolism abnormality caused by HFD, reflected by dramatically increasing the relative abundance of Muribaculaceae, Candidatus_Saccharimonas, and Bifidobacterium and production of short-chain fatty acids (SCFAs) and succinate. Interestingly, TP-induced BAT thermogenesis and iWAT browning were highly correlated with the reconstruction of the gut microbiome and formation of SCFAs and succinate. Collectively, these findings manifest beneficial actions of TP on the promotion of adipose browning and thermogenesis in association with gut microbiota reconstruction, and our findings may provide a promising way for preventing obesity.

Association of liver fibrosis-4 index with adverse outcomes in hypertrophic cardiomyopathy patients.

AIMS: The fibrosis-4 index (FIB-4) is a non-invasive tool to assess fibrosis risk in chronic liver disease. We aimed to explore the relationship between the FIB-4 index and long-term major adverse cardiovascular events (MACE) in HCM patients. METHODS AND RESULTS: Consecutive patients diagnosed with HCM were included. Patients were divided into two groups using a defined cutoff value established through a ROC analysis for predicting MACE (FIB-4 ≥ 2.37 and FIB-4 < 2.37). The final analysis comprised 187 HCM patients (34.8% females, 66.49 ± 11.43 years of age), with 47 (25.1%) in the FIB-4 ≥ 2.37 group and 140 (74.9%) in the FIB-4 < 2.37 group. Among these, 147 (78.6%) individuals had complete follow-up data. Patients with FIB-4 ≥ 2.37 demonstrated a higher prevalence of co-morbidities such as atrial fibrillation (27.7% vs. 7.9%; P < 0.001), heart failure (55.3% vs. 24.3%; P < 0.001), elevated NT-proBNP levels (3.03 ± 4.74 vs. 0.66 ± 1.08; P < 0.001), and lower LVEF (58.51 ± 7.86 vs. 61.84 ± 5.04; P = 0.001). Over a median of 41 (IQR 16-63) months follow-up, MACE occurred in 49 (33.3%), with a significantly higher incidence in the FIB-4 ≥ 2.37 group (58.8% vs. 25.7%, P < 0.001). Cardiac death rates were also elevated in the FIB-4 ≥ 2.37 group (20.6% vs. 2.7%, P = 0.001). Cox regression analysis revealed an independent association between FIB-4 ≥ 2.37 and a higher risk of MACE (adjusted HR: 1.919, 95% CI 1.015-3.630; P = 0.045) and cardiac death (adjusted HR: 9.518, 95% CI 1.718-52.732; P = 0.010). Furthermore, the FIB-4 index shows positive correlations with left atrium diameter (r = 0.229; P = 0.003), septal thickness (r = 0.231; P = 0.002), posterior wall thickness (r = 0.235; P = 0.001), and NT-proBNP (r = 0.271; P < 0.001). Conversely, a negative correlation was observed between the FIB-4 index and left ventricular ejection fraction (r = -0.185; P = 0.011). CONCLUSION: Elevated FIB-4 index, indicative of liver fibrosis, is independently associated with an increased risk of long-term MACE in HCM patients. This emphasizes the potential influence of liver function abnormalities on HCM prognosis, underscoring the need for comprehensive risk assessment in clinical management.

Corrigendum: Tracheal intubation in patients with Pierre Robin sequence: development, application, and clinical value based on a 3-dimensional printed simulator.

[This corrects the article DOI: 10.3389/fphys.2023.1292523.].

Bottle Nanomotors Amplify Tumor Oxidative Stress for Enhanced Calcium Overload/Chemodynamic Therapy.

Developing multifunctional, stimuli-responsive nanomedicine is intriguing because it has the potential to effectively treat cancer. Yet, poor tumor penetration of nanodrugs results in limited antitumor efficacy. Herein, an oxygen-driven silicon-based nanomotor (Si-motor) loaded with MnO and CaO2 nanoparticles is developed, which can move in tumor microenvironment (TME) by the cascade reaction of CaO2 and MnO. Under acidic TME, CaO2 reacts with acid to release Ca2+ to induce mitochondrial damage and simultaneously produces O2 and H2O2, when the loaded MnO exerts Fenton-like activity to produce ·OH and O2 based on the produced H2O2. The generated O2 drives Si-motor forward, thus endowing active delivery capability of the formed motors in TME. Meanwhile, MnO with glutathione (GSH) depletion ability further prevents reactive oxygen species (ROS) from being destroyed. Such TME actuated Si-motor with enhanced cellular uptake and deep penetration provides amplification of synergistic oxidative stresscaused by intracellular Ca2 + overloading, GSH depletion induced by Mn2+, and Mn2+ mediated chemodynamic treatment (CDT), leading to excellent tumor cell death. The created nanomotor may offer an effective platform for active synergistic cancer treatment.

Biogeography and dynamics of prokaryotic and microeukaryotic community assembly across 2600 km in the coastal and shelf ecosystems of the China Seas.

Marine prokaryotes and microeukaryotes are essential components of microbial food webs, and drive the biogeochemical cycling. However, the underlying ecological mechanisms driving prokaryotic and microeukaryotic community assembly in large-scale coastal ecosystems remain unclear. In this study, we studied biogeographic patterns of prokaryotic and microeukaryotic communities in the coastal and shelf ecosystem of the China Seas. Results showed that prokaryotic richness was the highest in the Yangtze River Plume, whereas microeukaryotic richness decreased from south to north. Prokaryotic-microeukaryotic co-occurrence networks display greater complexity in the Yangtze River Plume compared to other regions, potentially indicating higher environmental heterogeneity. Furthermore, the cross-domain networks revealed that prokaryotes were more interconnected with each other than with microeukaryotes or between microeukaryotes, and all hub nodes were bacterial taxa, suggesting that prokaryotes may be more important for sustaining the stability and multifunctionality of coastal ecosystem than microeukaryotes. Variation Partitioning Analysis revealed that approximately equal proportions of environmental, biotic and spatial factors contribute to variations in microbial community composition. Temperature was the primary environmental driver of both prokaryotic and microeukaryotic communities across the China Seas. Additionally, stochastic processes (dispersal limitation) and deterministic processes (homogeneous selection) were two major ecological factors in shaping microeukaryotic and prokaryotic assemblages, respectively, suggesting their different environmental plasticity and evolutionary mechanisms. Overall, these results demonstrate both prokaryotic and microeukaryotic communities displayed a latitude-driven distribution pattern and different assembly mechanisms, improving our understanding of microbial biogeography patterns under global change and anthropogenic activity driven habitat diversification in the coastal and shelf ecosystem.

PEDF-34 attenuates neurological deficit and suppresses astrocyte-dependent neuroinflammation by modulating astrocyte polarization via 67LR/JNK/STAT1 signaling pathway after subarachnoid hemorrhage in rats.

BACKGROUND: Reactive astrocytes participate in various pathophysiology after subarachnoid hemorrhage (SAH), including neuroinflammation, glymphatic-lymphatic system dysfunction, brain edema, BBB disruption, and cell death. Astrocytes transform into two new reactive phenotypes with changed morphology, altered gene expression, and secretion profiles, termed detrimental A1 and beneficial A2. This study investigates the effect of 67LR activation by PEDF-34, a PEDF peptide, on neuroinflammation and astrocyte polarization after the experimental SAH. METHODS: A total of 318 male adult Sprague-Dawley rats were used in experiments in vivo, of which 272 rats were subjected to the endovascular perforation model of SAH and 46 rats underwent sham surgery. 67LR agonist (PEDF-34) was administrated intranasally 1 h after SAH. 67LR-specific inhibitor (NSC-47924) and STAT1 transcriptional activator (2-NP) were injected intracerebroventricularly 48 h before SAH. Short- and long-term neurological tests, brain water content, immunostaining, Nissl staining, western blot, and ELISA assay were performed. In experiments in vitro, primary astrocyte culture with hemoglobin (Hb) stimulation was used to mimic SAH. The expression of the PEDF-34/67LR signaling pathway and neuro-inflammatory cytokines were assessed using Western blot, ELISA, and immunohistochemistry assays both in vivo and in vitro. RESULTS: Endogenous PEDF and 67LR expressions were significantly reduced at 6 h after SAH. 67LR was expressed in astrocytes and neurons. Intranasal administration of PEDF-34 significantly reduced brain water content, pro-inflammatory cytokines, and short-term and long-term neurological deficits after SAH. The ratio of p-JNK/JNK and p-STAT1/STAT1 and the expression of CFB and C3 (A1 astrocytes marker), significantly decreased after PEDF-34 treatment, along with fewer expression of TNF-α and IL-1ß at 24 h after SAH. However, 2-NP (STAT1 transcriptional activator) and NSC-47924 (67LR inhibitor) reversed the protective effects of PEDF-34 in vivo and in vitro by promoting A1 astrocyte polarization with increased inflammatory cytokines. CONCLUSION: PEDF-34 activated 67LR, attenuating neuroinflammation and inhibiting astrocyte A1 polarization partly via the JNK/STAT1 pathway, suggesting that PEDF-34 might be a potential treatment for SAH patients.

Sclerotinia rot of Zephyranthes candida caused by Sclerotinia sclerotiorum and Sclerotinia minor.

Sclerotinia rot is a serious disease that occurs on Zephyranthes candida. A thorough understanding of the pathogenic fungal species and understanding the biological characteristics are important for controlling sclerotinia. Fungal strains were isolated from the diseased leaves of Z. candida through tissue isolation. Koch's hypothesis screened pathogenic strains by pathogenicity of healthy leaves, including re-isolation and identification. A multigene phylogenetic tree was constructed by extracting genomic DNA from pathogenic strains and measuring the nucleotide sequences at four sites, including the internal transcribed spacer (ITS), RNA polymerase II second largest subunit (RPB2), glyceraldehyde-3-phosphate dehydrogenase (G3PDH), and heat shock protein 60 (HSP60). Morphological characteristics of the fungal structures were evaluated through microscopic analysis. The growth of pathogens was observed and recorded under different pH, different temperatures, different carbon sources and different nitrogen sources to clarify their biological characteristics. Representative strains D7, D13, X4, and X15 infected Z. candida and caused sclerotinia rot. At the beginning of the culture, white flocculent fungal hyphae appeared on the potato dextrose agar (PDA) medium, and black spherical to irregular-shaped sclerotia appeared at the edge of the colony after 7 days. The diameter of the sclerotia was 2.4-8.6 mm and 0.4-0.9 mm, respectively. One sclerotium was able to germinate from 1 to 5 apothecia. Ascus were cylindrical or spindle-shaped, with a size of 110.0-120.0 × 9.2-11.6 µm. One ascus contained eight colorless, oval ascospores, with a size of 8.4-12.0 × 4.5-5.5 µm. Based on the phylogenetic tree constructed with the gene sequences for ITS, G3PDH, HSP60, and RPB2, D7 and D13 shared 99% homology with sclerotinia sclerotiorum, whereas X4 and X15 shared 99% homology with sclerotinia minor. S. sclerotiorum growth was more suitable when the culture temperature was 15°C-25°C, pH 5.0, carbon source was maltose and nitrogen source was yeast powder. S. minor growth was more suitable when the culture temperature was 15°C, pH 5.0, the carbon source was glucose, and the nitrogen source was yeast powder. The results identified the pathogens as S. sclerotiorum and S. minor. To the best of our knowledge, this is the first report of S. sclerotiorum and S. minor causing sclerotinia rot on Z. candida. We herein aimed to identify the causal agent of sclerotinia rot of Z. candida in China based on morphological characteristics, molecular identification, and pathogenicity tests. Performed the experiments on the biological characteristics, to understand the law of disease occurrence. We also evaluated methods for the effective control of this disease. Our findings provide support for further studies on the pathogenesis mechanism of sclerotinia rot.

Predicting bowel function after diverting stoma closure in patients with rectal cancer.

Background: Patients with rectal cancer undergoing laparoscopic anterior resection and diverting stomas often suffer from bowel dysfunction after stoma closure, impairing their quality of life. This study aims to develop a machine learning tool to predict bowel function after diverting stoma closure. Methods: Clinicopathological data and post-operative follow-up information from patients with mid-low rectal cancer after diverting stoma closure were collected and analyzed. Patients were randomly divided into training and test sets in a 7:3 ratio. A machine learning model was developed in the training set to predict major low anterior resection syndrome (LARS) and evaluated in the test set. Decision curve analysis (DCA) was used to assess clinical utility. Results: The study included 396 eligible patients who underwent laparoscopic anterior resection and diverting stoma in Tongji Hospital affiliated with Huazhong University of Science and Technology from 1 January 2012 to 31 December 2020. The interval between stoma creation and closure, neoadjuvant therapy, and body mass index were identified as the three most crucial characteristics associated with patients experiencing major LARS in our cohort. The machine learning model achieved an area under the receiver operating characteristic curve (AUC) of 0.78 [95% confidence interval (CI): 0.74-0.83] in the training set (n=277) and 0.74 (95% CI: 0.70-0.79) in the test set (n=119), and area under the precision-recall curve (AUPRC) of 0.73 and 0.69, respectively, with sensitivity of 0.67 and specificity of 0.66 for the test set. DCA confirmed clinical applicability. Conclusions: This study developed a machine learning model to predict major LARS in rectal cancer patients after diverting stoma closure, aiding their decision-making and counseling.

Evaluation of vaccine candidates against Rhodococcus equi in BALB/c mice infection model: cellular and humoral immune responses.

Rhodococcus equi (R. equi) is a zoonotic opportunistic pathogen that mainly causes fatal lung and extrapulmonary abscesses in foals and immunocompromised individuals. To date, no commercial vaccine against R. equi exists. We previously screened all potential vaccine candidates from the complete genome of R. equi using a reverse vaccinology approach. Five of these candidates, namely ABC transporter substrate-binding protein (ABC transporter), penicillin-binding protein 2 (PBD2), NlpC/P60 family protein (NlpC/P60), esterase family protein (Esterase), and M23 family metallopeptidase (M23) were selected for the evaluation of immunogenicity and immunoprotective effects in BALB/c mice model challenged with R. equi. The results showed that all five vaccine candidate-immunized mice experienced a significant increase in spleen antigen-specific IFN-γ- and TNF-α-positive CD4 + and CD8 + T lymphocytes and generated robust Th1- and Th2-type immune responses and antibody responses. Two weeks after the R. equi challenge, immunization with the five vaccine candidates reduced the bacterial load in the lungs and improved the pathological damage to the lungs and livers compared with those in the control group. NlpC/P60, Esterase, and M23 were more effective than the ABC transporter and PBD2 in inducing protective immunity against R. equi challenge in mice. In addition, these vaccine candidates have the potential to induce T lymphocyte memory immune responses in mice. In summary, these antigens are effective candidates for the development of protective vaccines against R. equi. The R. equi antigen library has been expanded and provides new ideas for the development of multivalent vaccines.

In situ forest with lycopsid trees bearing lobed rhizomorphs from the Upper Devonian of Lincheng, China.

The earliest forests in the Devonian were reported from only four localities worldwide. The tree lycopsids, sometimes as the primary elements of Devonian forests, had evolved several types of rooting systems. In recent years, we found and excavated a Late Devonian (Famennian, 374-359 Ma) lycopsid forest from Zhejiang Province, China. The fossil forest occurs at seven locations of Lincheng Town of Changxing County and mainly consists of in situ small tree lycopsid (Heliodendron longshanense gen. et sp. nov.) stems usually connected to lobed cormose rhizomorphs. The four short lobes of each rhizomorph often branch once and bear roots arranged radially. Allometry is observed between the trunk diameter of Heliodendron and the length of its rhizomorphic lobes, indicating that the trunk develops later than the rhizomorph in tree lycopsid plants. The Devonian witnessed the transformation from clastic nonlycopsid dominated forests to Carboniferous swampy forests dominated by giant lycopsid trees. These trees form a multigenerational community, as shown by the in situ preserved stems at various levels within the same area due to frequent sedimentation events.

De Novo Synthesis of α-Ketoamides via Pd/TBD Synergistic Catalysis.

Precisely controlling the product selectivity of a reaction is an important objective in organic synthesis. α-Ketoamides are vital intermediates in chemical transformations and privileged motifs in numerous drugs, natural products, and biologically active molecules. The selective synthesis of α-ketoamides from feedstock chemicals in a safe and operationally simple manner under mild conditions is a long-standing catalysis challenge. Herein, an unprecedented TBD-switched Pd-catalyzed double isocyanide insertion reaction for assembling ketoamides in aqueous DMSO from (hetero)aryl halides and pseudohalides under mild conditions is reported. The effectiveness and utility of this protocol are demonstrated by its diverse substrate scope (93 examples), the ability to late-stage modify pharmaceuticals, scalability to large-scale synthesis, and the synthesis of pharmaceutically active molecules. Mechanistic studies indicate that TBD is a key ligand that modulates the Pd-catalyzed double isocyanide insertion process, thereby selectively providing the desired α-ketoamides in a unique manner. In addition, the imidoylpalladium(II) complex and α-ketoimine amide are successfully isolated and determined by X-ray analysis, confirming that they are probable intermediates in the catalytic pathway.

Study on the Prediction of Liver Injury in Acute Pancreatitis Patients by Radiomic Model Based on Contrast-Enhanced Computed Tomography.

OBJECTIVES: to predict liver injury in acute pancreatitis (AP) patients by establishing a radiomics model based on contrast-enhanced computed tomography (CECT). METHODS: a total of 1223 radiomic features were extracted from late arterial-phase pancreatic CECT images of 209 AP patients (146 in the training cohort and 63 in the test cohort), and the optimal radiomic features retained after dimensionality reduction by least absolute shrinkage and selection operator (LASSO) were used to construct a radiomic model through logistic regression analysis. In addition, clinical features were collected to develop a clinical model, and a joint model was established by combining the best radiomic features and clinical features to evaluate the practicality and application value of the radiomic models, clinical model and combined model. RESULTS: four potential features were selected from the pancreatic parenchyma to construct the radiomic model, and the area under the receiver operating characteristic curve (AUC) of the radiomic model was significantly greater than that of the clinical model for both the training cohort (0.993 vs. 0.653, p = 0.000) and test cohort (0.910 vs. 0.574, p = 0.000). The joint model had a greater AUC than the radiomics model for both the training cohort (0.997 vs. 0.993, p = 0.357) and test cohort (0.925 vs. 0.910, p = 0.302). CONCLUSIONS: the radiomic model based on CECT has good performance in predicting liver injury in AP patients and can guide clinical decision-making and improve the prognosis of patients with AP.

Uprighting and protraction of two unilateral mandibular molars using a cantilever arm through a sophisticated biomechanical system with clear aligner: A case report.

Although clear aligner can be efficient and predictable in some tooth movements, mandibular molar protraction is the least predictable owing to biological and biomechanical limitations. This case report presents a 20-year-old female with poor prognosed left mandibular first molar (#36), deviated dental midline and mild crowding. After extraction of #36, clear aligners and an Albert cantilever were used for treatment. Through carefully designed dual mechanical system, we achieved uprighting and protraction of #37 within 27 months, with crown and root movements of 9.9mm and 12.1mm, respectively. The predictability of the crown and root movement was 107.6% and 84.6%. Coincident dental and facial midline, class I molar and canine relationship and good root parallelism were also achieved. Large-distance mandibular molar protraction can be achieved effectively with a combination of Albert cantilever arm and clear aligner.

Preparation of environmentally responsive PDA&DOX@LAC live drug carrier for synergistic tumor therapy.

The development of intelligent, environmentally responsive and biocompatible photothermal system holds significant importance for the photothermal combined therapy of tumors. In this study, inspired by Lactobacillus (LAC), we prepared a biomimetic nanoplatform PDA&DOX@LAC for tumor photothermal-chemotherapy by integrating the chemotherapeutic drug doxorubicin (DOX) with dopamine through oxidative polymerization to form polydopamine (PDA) on the surface of LAC. The PDA&DOX@LAC nanoplatform not only achieves precise and controlled release of DOX based on the slightly acidic microenvironment of tumor tissues, but also exhibits enzyme-like properties to alleviate tumor hypoxia. Under near-infrared light irradiation, it effectively induces photothermal ablation of tumor cells, enhances cellular uptake of DOX with increasing temperature, and thus efficiently inhibits tumor cell growth. Moreover, it is further confirmed in vivo experiments that photothermal therapy combined with PDA&DOX@LAC induces tumor cells apoptosis, releases tumor-associated antigens, which is engulfed by dendritic cells to activate cytotoxic T lymphocytes, thereby effectively suppressing tumor growth and prolonging the survival period of 4T1 tumor-bearing mice. Therefore, the PDA&DOX@LAC nanoplatform holds immense potential in precise tumor targeting as well as photothermal combined therapy and provides valuable insights and theoretical foundations for the development of novel tumor treatment strategies based on endogenous substances within the body.

Establishing resilience-targeted prediction models of rainfall for transportation infrastructures for three demonstration regions in China.

Rainstorm is one of the global meteorological disasters that threaten the safety of transportation infrastructure and the connectivity of transportation system. Aiming to support the resilience assessment of transportation infrastructure in three representative regions: Sichuan-Chongqing, Yangtze River Delta, and Beijing-Tianjin-Hebei-Shandong, rainfall data over 40 years in the three regions are collected, and the temporal distribution of rainfall are analyzed. Prediction equations of rainfall are established. For the purpose of this, the probabilistic density function (PDF) is assigned to the rainfall by fitting the frequency distribution histogram. Using the assigned PDF, the rainfall data are transformed into standard normal space where regression of prediction equations is performed and the prediction accuracy is tested. The results show that: (1) The frequency of rainfall in the three regions follows a lognormal distribution based on which the prediction equations of rainfall can be established in standard normal space. The error of regression shows no remarkable dependence on self-variables, and the significance analysis indicates that the equations proposed in this paper are plausible for predicting rainfalls for the three regions. (2) The Yangtze River Delta region has a higher risk of rainstorm disaster compared to the other two regions according to the frequency of rainfall and the return period of precipitation concentration. (3) Over the period of 1980-2021, the Sichuan-Chongqing region witnessed an increase in yearly rainfall but a decrease in rainstorm disasters, whereas the other two regions experienced a consistent rise in both metrics.