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Esophageal cancer (EC) is one of the most common aggressive malignant tumors in the digestive system with a severe epidemiological situation and poor prognosis. The early diagnostic rate of EC is low, and most EC patients are diagnosed at an advanced stage. Multiple multimodality treatments have gradually evolved into the main treatment for advanced EC, including surgery, chemotherapy, radiotherapy, targeted therapy, and immunotherapy. And the emergence of targeted therapy and immunotherapy has greatly improved the survival of EC patients. This review highlights the latest advances in targeted therapy and immunotherapy for EC, discusses the efficacy and safety of relevant drugs, summarizes related important clinical trials, and tries to provide references for therapeutic strategy of EC.

•Post-stroke basal ganglia aphasia (PSBGA) manifests as an atypical language disorder accompanied by emotional and cognitive impairments.•The pathogenesis of PSBGA includes damage to the limbic pathways, dorsally located tracts in the left hemisphere, and left basal ganglia pathways.•New roles played by corpus callosum forceps minor in language processing are identified. Stroke often damages the basal ganglia, leading to atypical and transient aphasia, indicating that post-stroke basal ganglia aphasia (PSBGA) may be related to different anatomical structural damage and functional remodeling rehabilitation mechanisms. The basal ganglia contain dense white matter tracts (WMTs). Hence, damage to the functional tract may be an essential anatomical structural basis for the development of PSBGA. We first analyzed the clinical characteristics of PSBGA in 28 patients and 15 healthy controls (HCs) using the Western Aphasia Battery and neuropsychological test batteries. Moreover, we investigated white matter injury during the acute stage using diffusion magnetic resonance imaging scans for differential tractography. Finally, we used multiple regression models in correlation tractography to analyze the relationship between various language functions and quantitative anisotropy (QA) of WMTs. Compared with HCs, patients with PSBGA showed lower scores for fluency, comprehension (auditory word recognition and sequential commands), naming (object naming and word fluency), reading comprehension of sentences, Mini-Mental State Examination, and Montreal Cognitive Assessment, along with increased scores in Hamilton Anxiety Scale-17 and Hamilton Depression Scale-17 within 7 days after stroke onset (P < 0.05). Differential tractography revealed that patients with PSBGA had damaged fibers, including in the body fibers of the corpus callosum, left cingulum bundles, left parietal aslant tracts, bilateral superior longitudinal fasciculus II, bilateral thalamic radiation tracts, left fornix, corpus callosum tapetum, and forceps major, compared with HCs (FDR < 0.02). Correlation tractography highlighted that better comprehension was correlated with a higher QA of the left inferior fronto-occipital fasciculus (IFOF), corpus callosum forceps minor, and left extreme capsule (FDR < 0.0083). Naming was positively associated with the QA of the left IFOF, forceps minor, left arcuate fasciculus, and uncinate fasciculus (UF) (FDR < 0.0083). Word fluency of naming was also positively associated with the QA of the forceps minor, left IFOF, and thalamic radiation tracts (FDR < 0.0083). Furthermore, reading was positively correlated with the QA of the forceps minor, left IFOF, and UF (FDR < 0.0083). PSBGA is primarily characterized by significantly impaired word fluency of naming and preserved repetition abilities, as well as emotional and cognitive dysfunction. Damaged limbic pathways, dorsally located tracts in the left hemisphere, and left basal ganglia pathways are involved in PSBGA pathogenesis. The results of connectometry analysis further refine the current functional localization model of higher-order neural networks associated with language functions.

Gastric cancer (GC) is one of the most common malignant tumors worldwide. Its incidence ranks the 5th among all malignant tumors globally, and it is the 3rd leading cause of death among patients with cancer. Surgical treatment is the first choice in clinical practice. However, targeted therapy, immunotherapy, and other treatment methods have also become research hotspots at home and abroad with the development of individualized precision therapy in recent years, besides traditional radiotherapy and chemotherapy. At present, targeted therapy and immunotherapy are methods used for treating GC, and they have important clinical application value and prospects. This study aimed to review the research progress of targeted therapy and immunotherapy for GC, focusing on its mechanism of action and related important clinical trials, hoping to provide references for the clinical treatment of GC.

Apple (Malus × domestica) trees are vulnerable to freezing temperatures. However, there has been only limited success in developing cold-hardy cultivars. This lack of progress is due at least partly to lack of understanding of the molecular mechanisms of freezing tolerance in apple. In this study, we evaluated the potential roles for two R2R3 MYB transcription factors (TFs), MYB88 and the paralogous FLP (MYB124), in cold stress in apple and Arabidopsis. We found that MYB88 and MYB124 positively regulate freezing tolerance and cold-responsive gene expression in both apple and Arabidopsis. Chromatin-Immunoprecipitation-qPCR and electrophoretic mobility shift assays showed that MdMYB88/MdMYB124 act as direct regulators of the COLD SHOCK DOMAIN PROTEIN 3 (MdCSP3) and CIRCADIAN CLOCK ASSOCIATED 1 (MdCCA1) genes. Dual luciferase reporter assay indicated that MdCCA1 but not MdCSP3 activated the expression of MdCBF3 under cold stress. Moreover, MdMYB88 and MdMYB124 promoted anthocyanin accumulation and H2O2 detoxification in response to cold. Taken together, our results suggest that MdMYB88 and MdMYB124 positively regulate cold hardiness and cold-responsive gene expression under cold stress by C-REPEAT BINDING FACTOR (CBF)-dependent and CBF-independent pathways.

In order to reduce the effect of nonlinear friction and time-varying factors on the servo system of a computer numerical control (CNC) machine tool and improve its motion control accuracy, this paper uses an adaptive sliding mode control (ASMC) method based on model reference adaptive control (MRAC). The method adopts ASMC in the control outer loop and obtains the optimal control parameters by making the sliding mode control (SMC) law continuous and adaptively estimating the control parameters. At the same time, MRAC is used in the control inner loop to enhance the “invariance” of the controlled object so that the switching gain of SMC can satisfy the disturbance matching condition even under lesser conditions. Simulation and experimental results show that compared with the traditional SMC, the ASMC based on MRAC proposed in this paper effectively reduces the influence of nonlinear friction on the system performance, and the reduction in following error reaches 71.2%, which significantly improves the motion control accuracy of the control system. The spectral analysis of the following errors shows that the maximum magnitude reduction rate of the high-frequency chattering is 89.02%, which significantly reduces the effect of the high-frequency chattering and effectively improves the stability performance of the control system.

The predictive skill of summer sea ice concentration (SIC) in the Arctic presents a steep decline when initialized before June, which is the so‐called spring predictability barrier for Arctic sea ice. This study explores the potential influence of surface heat flux, cloud and water vapor anomalies on monthly to seasonal predictions of Arctic SIC anomalies. The results show an enhancement in skill predicting Arctic September SIC in the models that use surface fluxes, clouds, or water vapor in combination with SIC and surface sea temperature as predictors when initialized in boreal spring. This result shows the potential to reduce the spring barrier for Arctic SIC predictions by including the surface heat budget. The enhanced predictive skill can be very likely linked to the improved representation of the thermodynamics associated with water vapor and cloudiness anomalies in spring. Plain Language Summary Under the influence of climate change, the summer sea ice extent in the Arctic presents significant variability and thus is crucial to human activities in the Arctic. However, the predictive skill for summer sea ice in the Arctic shows a steep decline when predictions are initiated before June, which is called the spring barrier. In this study, we show that adding surface heat fluxes (net surface heat flux, net surface long wave radiation and net surface shortwave radiation), clouds or water vapor into a statistical prediction model can better represent the interactive processes at the atmosphere and ocean interface. The enhancement improves the predictive skill of summer sea ice in the Arctic and reduces the spring barrier, especially in areas of the Beaufort Sea, Chukchi Sea, and Central Arctic. Key Points The predictive skill of summer Arctic sea ice using statistical prediction models presents a steep decline initialized before June The spring barrier can be reduced, but not eliminated, by using spring surface heat fluxes in combination with sea ice concentration and sea surface temperature The statistical models using surface heat fluxes help to improve representation of thermodynamics associated with water vapor and cloudiness

A comprehensive transcriptomic survey of pigs can provide a mechanistic understanding of tissue specialization processes underlying economically valuable traits and accelerate their use as a biomedical model. Here we characterize four transcript types (lncRNAs, TUCPs, miRNAs, and circRNAs) and protein-coding genes in 31 adult pig tissues and two cell lines. We uncover the transcriptomic variability among 47 skeletal muscles, and six adipose depots linked to their different origins, metabolism, cell composition, physical activity, and mitochondrial pathways. We perform comparative analysis of the transcriptomes of seven tissues from pigs and nine other vertebrates to reveal that evolutionary divergence in transcription potentially contributes to lineage-specific biology. Long-range promoter–enhancer interaction analysis in subcutaneous adipose tissues across species suggests evolutionarily stable transcription patterns likely attributable to redundant enhancers buffering gene expression patterns against perturbations, thereby conferring robustness during speciation. This study can facilitate adoption of the pig as a biomedical model for human biology and disease and uncovers the molecular bases of valuable traits. A comprehensive transcriptomic survey of the pig could enable mechanistic understanding of tissue specialization and accelerate its use as a biomedical model. Here the authors characterize four distinct transcript types in 31 adult pig tissues to dissect their distinct structural and transcriptional features and uncover transcriptomic variability related to tissue physiology.

Edible plant-derived exosome-like nanoparticles (EPDELNs) are novel naturally occurring plant ultrastructures that are structurally similar to exosomes. Many EPDELNs have anti-inflammatory properties. MicroRNAs (miRNAs) play a critical role in mediating physiological and pathological processes in animals and plants. Although miRNAs can be selectively encapsulated in extracellular vesicles, little is known about their expression and function in EPDELNs. In this study, we isolated nanovesicles from 11 edible fruits and vegetables and subjected the corresponding EPDELN small RNA libraries to Illumina sequencing. We identified a total of 418 miRNAs—32 to 127 per species—from the 11 EPDELN samples. Target prediction and functional analyses revealed that highly expressed miRNAs were closely associated with the inflammatory response and cancer-related pathways. The 418 miRNAs could be divided into three classes according to their EPDELN distributions: 26 “frequent” miRNAs (FMs), 39 “moderately present” miRNAs (MPMs), and 353 “rare” miRNAs (RMs). FMs were represented by fewer miRNA species than RMs but had a significantly higher cumulative expression level. Taken together, our in vitro results indicate that miRNAs in EPDELNs have the potential to regulate human mRNA.

Lipids are vital biomolecules involved in the formation of various biofilms. Seizures can cause changes in lipid metabolism in the brain. In-depth studies at multiple levels are urgently needed to elucidate lipid composition, distribution, and metabolic pathways in the brain after seizure. In this research, a cutting-edge targeted quantitative lipidomics study was conducted on the hippocampal tissues of six rats with temporal lobe epilepsy and six normal rats. Accurate lipid quantification based on linear equations was calculated using an internal standard. The lipids were quantitatively and qualitatively analyzed by ultra-high performance liquid chromatography (UPLC) and mass spectrometry (MS). A total of 21 lipid classes were identified. Among them, the most abundant were triacylglycerol (TG), phosphatidyl ethanolamine (PE-P), and fatty acids (FA). Cholesteryl ester (ChE) exhibits the most considerable difference between the normal and epileptic samples. ChE was found to be the most significantly upregulated lipid, while FA was observed to be the most significantly downregulated lipid. Based on the absolute quantitative analysis of lipids in rat hippocampal specimens, the contents and change trends of different lipids were observed. Upregulation of ChE and dihydroceramide (DHCer) was observed, and an analysis of the distribution changes elucidated the causes and possible molecular mechanisms of lipid accumulation in temporal lobe epilepsy. The results and methods described provide a comprehensive analysis of lipid metabolism in temporal lobe epilepsy and a new therapeutic target for the treatment of epilepsy.

A key challenge in lake ice modeling is quantifying the heat flux from water to ice. In shallow Central Asian lakes, where the seasonal ice cover mainly consists of columnar congelation ice, sunlight penetration enables strong interactions between ice and water. The evolution of ice cover in Lake Ulansu (Ulansuhai, Wuliangsuhai) in northern China was investigated via the High‐resolution Thermodynamic Snow and Ice (HIGHTSI) model. Atmospheric forcing was provided by calibrated ERA5 reanalysis data, and the initial freeze‐up dates were identified from remote sensing observations. A new parameterization of the water–ice heat flux (Fw), which is suitable for shallow lakes, was proposed as Fw = aQsw + b, where Qsw represents the solar heating of water and a and b are fitted coefficients. The model showed high correlations (>0.9) and low errors (<5 cm for ice thickness; <2°C for ice temperature) with respect to field observations. Throughout the ice season, long‐ and shortwave radiation promoted ice growth and melting, respectively. Surface melting and sublimation accounted for 9.5% and 9.8%, respectively, of the total ice decay, and the water–ice heat flux Fw = −17.5 ± 13.0 W m−2 was critical for simulation accuracy. Furthermore, despite the shallow depth, the lake released over 100 W m−2 of heat into the atmosphere for 2 days after break‐up. These findings highlight the climatic sensitivity and support sustainable water resource management of more than 10,000 shallow lakes in Central Asia.