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Phage-immunoprecipitation sequencing (PhIP-Seq) technology is an innovative, high-throughput antibody detection method. It enables comprehensive analysis of individual antibody profiles. This technology shows great potential, particularly in exploring disease mechanisms and immune responses. Currently, PhIP-Seq has been successfully applied in various fields, such as the exploration of biomarkers for autoimmune diseases, vaccine development, and allergen detection. A variety of bioinformatics tools have facilitated the development of this process. However, PhIP-Seq technology still faces many challenges and has room for improvement. Here, we review the methods, applications, and challenges of PhIP-Seq and discuss its future directions in immunological research and clinical applications. With continuous progress and optimization, PhIP-Seq is expected to play an even more important role in future biomedical research, providing new ideas and methods for disease prevention, diagnosis, and treatment.

Abstract Background To compare the dosimetric quality of three widely used techniques for LINAC-based single-isocenter multi-target multi-fraction stereotactic radiosurgery (fSRS) with more than 20 targets: dynamic conformal arc (DCA) in BrainLAB Multiple Metastases Elements (MME) module and volumetric modulated arc therapy (VMAT) using RapidArc (RA) and HyperArc (HA) in Varian Eclipse. Methods Ten patients who received single-isocenter fSRS with 20–37 targets were retrospectively replanned using MME, RA, and HA. Various dosimetric parameters, such as conformity index (CI), Paddick CI, gradient index (GI), normal brain dose exposures, maximum organ-at-risk (OAR) doses, and beam-on times were extracted and compared among the three techniques. Wilcoxon signed-rank test was used for statistical analysis. Results All plans achieved the prescribed dose coverage goal of at least 95% of the planning target volume (PTV). HA plans showed superior conformity compared to RA and MME plans. MME plans showed superior GI compared to RA and HA plans. RA plans resulted in significantly higher low and intermediate dose exposure to normal brain compared to HA and MME plans, especially for lower doses of ≥ 8Gy and ≥ 5Gy. No significant differences were observed in the maximum dose to OARs among the three techniques. The beam-on time of MME plans was about two times longer than RA and HA plans. Conclusions HA plans achieved the best conformity, while MME plans achieved the best dose fall-off for LINAC-based single-isocenter multi-target multi-fraction SRS with more than 20 targets. The choice of the optimal technique should consider the trade-offs between dosimetric quality, beam-on time, and planning effort.

Abstract Background The widespread utilization of chest High-resolution Computed Tomography (HRCT) has prompted detection of pulmonary ground-glass nodules (GGNs) in otherwise asymptomatic individuals. We aimed to establish a simple clinical risk score model for assessing GGNs based on HRCT. Methods We retrospectively analyzed 574 GGNs in 574 patients undergoing HOOK-WIRE puncture and pulmonary nodule surgery from January 2014 to November 2018. Clinical characteristics and imaging features of the GGNs were assessed. We analyzed the differences between malignant and benign nodules using binary logistic regression analysis and constructed a simple risk score model, the VBV Score, for predicting the malignancy status of GGNs. Then, we validated this model via other 1200 GGNs in 1041 patients collected from three independent clinical centers in 2022. Results For the exploratory phase of this study, out of the 574 GGNs, 481 were malignant and 93 were benign. Vacuole sign, air bronchogram, and intra-nodular vessel sign were important indicators of malignancy in GGNs. Then, we derived a VBV Score = vacuole sign + air bronchogram + intra-nodular vessel sign, to predict the malignancy of GGNs, with a sensitivity, specificity, and accuracy of 95.6%, 80.6%, and 93.2%, respectively. We also validated it on other 1200 GGNs, with a sensitivity, specificity, and accuracy of 96.0%, 82.6%, and 95.0%, respectively. Conclusions Vacuole sign, air bronchogram, and intra-nodular vessel sign were important indicators of malignancy in GGNs. VBV Score showed good sensitivity, specificity, and accuracy for differentiating benign and malignant pulmonary GGNs.

Purpose: To investigate the relationship between normal brain exposure in LINAC-based single-isocenter multitarget multifraction stereotactic radiosurgery or stereotactic radiation therapy (SRT) and the number or volume of treated brain metastases, especially for high numbers of metastases. Methods and Materials: A cohort of 44 SRT patients with 709 brain metastases was studied. Renormalizing to a uniform prescription of 27 Gy in 3 fractions, normal brain dose volume indices, including V23 Gy (volume receiving >23 Gy), V18 Gy (volume receiving >18 Gy), and mean dose, were evaluated on these plans against the number and the total volume of targets for each plan. To compare with exposures from whole-brain radiation therapy (WBRT), the SRT dose distributions were converted to equivalent dose in 3 Gy fractions (EQD3) using an alpha-beta ratio of 2 Gy. Results: With increasing number of targets and increasing total target volume, normal brain exposures to dose ≥18 Gy increases, and so does the mean normal brain dose. The factors of the number of targets and the total target volume are both significant, although the number of targets has a larger effect on the mean normal brain dose and the total target volume has a larger effect on V23 Gy and V18 Gy. The EQD3 mean normal brain dose with SRT planning is lower than conventional WBRT. On the other hand, SRT results in higher hot spot (ie, maximum dose outside of tumor) EQD3 dose than WBRT. Conclusions: Based on clinical SRT plans, our study provides information on correlations between normal brain exposure and the number and total volume of targets. As SRT becomes more greatly used for patients with increasingly extensive brain metastases, more clinical data on outcomes and toxicities is necessary to better define the normal brain dose constraints for high-exposure cases and to optimize the SRT management for those patients.

Fe-based Fischer-Tropsch Synthesis (FTS) enables the selective conversion of syngas into long-chain hydrocarbons, which can be further refined to produce highly demanded liquid fuels and high-value chemical products. However, developing novel heterogeneous catalysts for FTS with desirable performance characteristics is a challenging task, as their performance depends on various factors such as precursor, support material, promoters, pretreatment conditions and the catalyst structures. Thus, it remains difficult to understand the structure-performance relationship of FTS and to optimize the catalyst formulations and operating conditions rationally. By integrating traditional chemistry with machine learning, we herein establish intrinsic correlations among reduction, reaction conditions, phase information and the methane selectivity of Fe-based FTS, using high quality experimental data. The content of the iron phases in the post-reaction phase, particularly χ-Fe5C2, significantly influences the methane selectivity of the catalyst. Four types of additives K, Cu, SiO2, and Ca could effectively suppress the methane selectivity, most likely by promoting or stabilizing the iron carbide phases, indicated by their strong correlation. The machine learned structure-performance relationships offers new insights into the design of Fe-based FTS catalysts, and could guide the further optimization of the preprocessing conditions and various parameter factors to minimize the methane selectivity of FTS.

Abstract Background Locally advanced non-small cell lung cancer (NSCLC) with N1/N2 lymph node metastasis is challenging with poor survival. Neo-adjuvant chemo-immunotherapy has gained benefits in a proportion of these patients. However no specific biomarker has been proved to predict the effect before therapy. In addition, the relationship of nodal status and survival after neo-adjuvant chemo-immunotherapy is still not well stated. Methods A total of 75 resectable NSCLC patients with N1/N2 stage who received neo-adjuvant chemo-immunotherapy plus surgery were retrospectively studied. The clinical characteristics, surgical information and safety parameters were collected. The correlations of major pathological response (MPR) and pathological complete response (pCR) with clinical data were analyzed. The progression free disease(PFS) and overall survival(OS) were evaluated with pathological response and nodal status. Results Of the 75 patients, 69 (92%) patients experienced treatment related adverse effects, while grade 3–4 adverse effects occurred in 8 (10%) patients. All the patients received surgical R0 resection with a MPR rate of 60% and a pCR rate of 36%. 67% of N1 patients and 77% of N2 patients had nodal clearance after neo-adjuvant treatment. A significant difference was observed between pathological response with age, histology and multiple lymph node metastasis. The PFS was better in the MPR cohort. The PFS was 90.1% and 83.6% at the nodal clearance group at the time of 12 and 18 months, compared with 70.1% and 63.7% at the nodal residual group. Conclusions The neo-adjuvant chemo-immunotherapy for locally advanced NSCLC with nodal positive was safe and feasible. The patients with elder age and squamous-cell carcinoma (SCC) were more likely to have better pathological response, while multiple nodal metastasis was a negative predictor. The clearance of lymph node resulted in significantly longer PFS and OS.

K418 alloy was prepared by selective laser melting (SLM) at different laser powers (160∼240 W) in this paper. The influence of laser power on the densification behavior, microstructure, microhardness, and tensile properties was studied systematically. The results showed that the densities of the material increased rapidly first and then decreased slowly with the increase of laser power. When the laser power increased from 160 W to 240 W, the surface defects of the specimen decreased, the microstructure changed from columnar dendrites to cellular, and the grains grew in the direction preferentially. When the laser power is 200 W, the grain size is the smallest, the content of small-angle grain boundaries is more, the Schmidt factor is less, and then the best mechanical properties are achieved, at which the microhardness reaches 362.89 ± 5.01 HV, the tensile strength reaches 1244.35 ± 70.1 MPa, the yield strength reaches 863.89 ± 23.1 MPa, and the elongation of the material reaches a maximum of 12.53 ± 0.71 %. In addition, the fracture mode of the material is a mixed tough-brittle fracture mechanism.

The impact of short-term exposure to air pollutants on the morbidity of schizophrenia, particularly in low- and middle-income countries, remains inadequately explored. The objective of this research was to investigate the relationship between short-term exposure to ambient air pollutants and the risk of schizophrenia hospitalization in Jingmen, China. We performed a time-stratified case-crossover study using daily records of hospital admissions due to schizophrenia in Jingmen Mental Health Center from 2015 to 2017. Environmental exposures to air pollutants and meteorological conditions on case and control days were estimated on the basis of measurements from ground monitoring stations. To investigate the relationship between short-term exposure to ambient air pollutants and the risk of hospitalization for schizophrenia, a conditional logistic regression model was employed. We performed subgroup analyses stratified according to sex, age groups, and season. In total, 4079 schizophrenia hospitalizations were recorded during the designated period. Increased risk of schizophrenia was merely associated with short-term exposure to SO2 and NO2. The estimated odds per interquartile range (IQR) increase in exposure was 1.112 (95% confidence interval (CI): 1.033, 1.196) for SO2 (IQR = 12 µg/m3) and 1.112 (95% CI: 1.033, 1.197) for NO2 (IQR = 18 µg/m3) on lag-0 day. Greater air pollution-schizophrenia associations were observed among middle-aged and older adults (over 45 years of age) and during the cold season. This study added case-crossover evidence indicating that short-term exposure to ambient air pollution, specifically SO2 and NO2, is linked to a higher risk of hospital admissions for schizophrenia. These findings contribute to a better understanding of the detrimental effects of air pollution on neuropsychiatric health conditions.

The solid electrolyte Li10GeP2S12 (LGPS) plays a crucial role in the development of all-solid-state batteries and has been widely studied both experimentally and theoretically. The properties of solid electrolytes, such as thermodynamic stability, conductivity, band gap, and more, are closely related to their ground-state structures. However, the presence of site-disordered co-occupancy of Ge/P and defective fractional occupancy of lithium ions results in an exceptionally large number of possible atomic configurations (structures). Currently, the electrostatic energy criterion is widely used to screen favorable candidates and reduce computational costs in first-principles calculations. In this study, we employ the machine learning- and active-learning-based LAsou method, in combination with first-principles calculations, to efficiently predict the most stable configuration of LGPS as reported in the literature. Then, we investigate the diffusion properties of Li ions within the temperature range of 500–900 K using ab initio molecular dynamics. The results demonstrate that the atomic configurations with different skeletons and Li ion distributions significantly affect the Li ions’ diffusion. Moreover, the results also suggest that the LAsou method is valuable for refining experimental crystal structures, accelerating theoretical calculations, and facilitating the design of new solid electrolyte materials in the future.

In this work, high performance InAlN/GaN HEMT based on the n+GaN regrown ohmic contact with n+GaN contact ledge structure is proposed. The regrown ohmic contact of InAlN/GaN HEMT is formed by MBE n+GaN regrowth and self-stopping etching, which makes the total ohmic contact resistance between the 2DEG channel and the ohmic metal decrease to $0.12 \Omega \cdot $ mm and forms n+GaN contact ledge structure. Owing to the n+GaN contact ledge on the InAlN barrier, with the increasing of drain-source voltage (VDS), an additional current path comes into being between the n+GaN contact ledge on the InAlN barrier and the 2DEG channel, which can “shorten” the device effective drain-source distance, thus further reducing the parasitic resistance. Compared with regrown InAlN/GaN HEMT without n+GaN contact ledge structure, the peak transconductance (Gm.max) of regrown InAlN/GaN HEMT with n+GaN contact ledge structure increases from 747 mS/mm to 874 mS/mm, and the saturation current density (ID.max) increases from 2.6 A/mm to 2.9 A/mm. Besides, the self-stopping etching on the access region does not induce extra defects, and negligible current collapse is obtained. As the results of low parasitic resistance, high output current density, low knee voltage and negligible current collapse, power-added-efficiency (PAE) of 44% together with output power density (Pout) of 2.5 W/mm is achieved at 30 GHz and $V_{\mathrm{ DS}}$ of 10 V, which indicates regrown InAlN/GaN HEMT with n+GaN contact ledge structure has great potential for millimeter-wave low voltage applications. Additionally, the transfer and schottky gate characteristics show negligible degradation after OFF/ON-state electrical stress tests.

Abstract Chemical-disordered materials have a wide range of applications whereas the determination of their structures or configurations is one of the most important and challenging problems. Traditional methods are extremely inefficient or intractable for large systems due to the notorious exponential-wall issue that the number of possible structures increase exponentially for N-body systems. Herein, we introduce an efficient approach to predict the thermodynamically stable structures of chemical-disordered materials via active-learning accompanied by first-principles calculations. Our method, named LAsou, can efficiently compress the sampling space and dramatically reduce the computational cost. Three distinct and typical finite-size systems are investigated, including the anion-disordered BaSc(OxF1−x)3 (x = 0.667), the cation-disordered Ca1−xMnxCO3 (x = 0.25) with larger size and the defect-disordered ε-FeCx (x = 0.5) with larger space. The commonly used enumeration method requires to explicitly calculate 2664, 1033, and 10496 configurations, respectively, while the LAsou method just needs to explicitly calculate about 15, 20, and 10 configurations, respectively. Besides the finite-size system, our LAsou method is ready for quasi-infinite size systems empowering materials design.

This study investigates the interdecadal change in the covariability between the Tibetan Plateau (TP) east–west dipole precipitation and Indian precipitation during summer and primarily explores the modulation of atmospheric circulation anomalies on the covariability. The results reveal that the western TP precipitation (WTPP), eastern TP precipitation (ETPP), and northwestern Indian precipitation (NWIP) have covariability, with an in-phase variation between the WTPP and NWIP and an out-of-phase variation between the WTPP and ETPP. Moreover, this covariability was unclear during 1981–2004 and became significant during 2005–2019, showing a clear interdecadal change. During 2005–2019, a thick geopotential height anomaly, which tilted slightly northward, governed the TP, forming upper- and lower-level coupled circulation anomalies (i.e., anomalous upper-level westerlies over the TP and lower-level southeasterlies and northeasterlies around the southern flank of the TP). As such, the upper- and lower-tropospheric circulation anomalies synergistically modulate the summer WTPP, ETPP, and NWIP, causing the covariability of summer precipitation over the TP and India during 2005–2019. The upper- or lower-level circulation anomalies cannot independently result in significant precipitation covariability. During 1981–2004, the upper- and lower-level circulation anomalies were not strongly coupled, which caused precipitation non-covariability. The sea surface temperature anomalies (SSTAs) in the western North Pacific (WNP) and tropical Atlantic (TA) may synergistically modulate the upper- and lower-level coupled circulation anomalies, contributing to the covariability of the WTPP, ETPP, and NWIP during 2005–2019. The modulation of the WNP and TA SSTs on the coupled circulation anomalies was weaker during 1981–2004, which was therefore not conducive to this precipitation covariability. This study may provide valuable insights into the characteristics and mechanisms of spatiotemporal variation in summer precipitation over the TP and its adjacent regions, thus offering scientific support for local water resource management, ecological environment protection, and social and economic development.

Abstract Background Dysregulated activation of the inflammasome is involved in various human diseases including acute cerebral ischemia, multiple sclerosis and sepsis. Though many inflammasome inhibitors targeting NOD-like receptor protein 3 (NLRP3) have been designed and developed, none of the inhibitors are clinically available. Growing evidence suggests that targeting apoptosis-associated speck-like protein containing a CARD (ASC), the oligomerization of which is the key event for the assembly of inflammasome, may be another promising therapeutic strategy. Lonidamine (LND), a small-molecule inhibitor of glycolysis used as an antineoplastic drug, has been evidenced to have anti-inflammation effects. However, its anti-inflammatory mechanism is still largely unknown. Methods Middle cerebral artery occlusion (MCAO), experimental autoimmune encephalomyelitis (EAE) and LPS-induced sepsis mice models were constructed to investigate the therapeutic and anti-inflammasome effects of LND. The inhibition of inflammasome activation and ASC oligomerization by LND was evaluated using western blot (WB), immunofluorescence (IF), quantitative polymerase chain reaction (qPCR) and enzyme-linked immunosorbent assay (ELISA) in murine bone marrow-derived macrophages (BMDMs). Direct binding of LND with ASC was assessed using molecular mock docking, surface plasmon resonance (SPR), and drug affinity responsive target stability (DARTS). Results Here, we find that LND strongly attenuates the inflammatory injury in experimental models of inflammasome-associated diseases including autoimmune disease-multiple sclerosis (MS), ischemic stroke and sepsis. Moreover, LND blocks diverse types of inflammasome activation independent of its known targets including hexokinase 2 (HK2). We further reveal that LND directly binds to the inflammasome ligand ASC and inhibits its oligomerization. Conclusions Taken together, our results identify LND as a broad-spectrum inflammasome inhibitor by directly targeting ASC, providing a novel candidate drug for the treatment of inflammasome-driven diseases in clinic.

An elite hexaploid triticale Yukuri from Australia was used as a bridge for transferring valuable genes from Secale cereale L. into common wheat for enriching the genetic variability of cultivated wheat. Non-denaturing-fluorescence in situ hybridization (ND-FISH) identified that Yukuri was a secondary triticale with a complete set of rye chromosomes and a 6D(6A) substitution. Seed protein electrophoresis showed that Yukuri had a unique composition of glutenin subunits. A set of Yukuri-derived wheat-rye introgression lines were created from a Yukuri x wheat population, and all lines were identified by ND-FISH with multiple probes and validated by diagnostic molecular marker analysis. A total of 59 wheat-rye introgression lines including modified chromosome structural variations of wheat, and new complex recombinant chromosomes of rye were detected through ND-FISH and Oligo-FISH painting based on oligonucleotide pools derived from wheat-barley genome collinear regions. Wheat lines carrying the 1R chromosome from Yukuri displayed resistance to both stripe rust and powdery mildew, while the lines carrying the 3RL and 7RL chromosome arms showed stripe rust resistance. The chromosome 1R-derived lines were found to exhibit a significant effect on most of the dough-related parameters, and chromosome 5R was clearly associated with increased grain weight. The development of the wheat-rye cytogenetic stocks carrying disease resistances and superior agronomic traits, as well as the molecular markers and FISH probes will promote the introgression of abundant variation from rye into wheat improvement programs.

Mapping and monitoring cluster morphology provides insights for disease risk assessment, quality control in wine production, and understanding environmental influences on cluster shape. During the progression of grapevine morphology, cluster closure (CC) (also called bunch closure) is the stage when berries touch one another. This study used mobile phone images to develop a direct quantification method for tracking CC in three grapevine cultivars (Riesling, Pinot gris, and Cabernet Franc). A total of 809 cluster images from fruit set to veraison were analyzed using two image segmentation methods: (i) a Pyramid Scene Parsing Network (PSPNet) to extract cluster boundaries and (ii) Otsu’s image thresholding method to calculate % CC based on gaps between the berries. PSPNet produced high accuracy (mean accuracy = 0.98, mean intersection over union (mIoU) = 0.95) with mIoU > 0.90 for both cluster and noncluster classes. Otsu’s thresholding method resulted in

Abstract GSDMD is the key effector of pyroptosis, but its non-pyroptosis-related functions have seldom been reported. Here, we report that GSDMD is overexpressed in different types of tumours, including head and neck squamous-cell carcinoma, and it promotes the sensitivity of tumour cells to cisplatin. Unexpectedly, the enhanced cisplatin sensitivity is mediated by apoptosis but not pyroptosis, the well-known function of GSDMD. Furthermore, we found that GSDMD can activate the unfolded protein response by promoting the phosphorylation of eIF2α. Mechanistically, we demonstrated that GSDMD can directly bind to eIF2α and enhance the interaction between eIF2α and its upstream kinase PERK, leading to eIF2α phosphorylation. Consequently, the protein levels of ATF-4 were upregulated, downstream apoptosis-related proteins such as CHOP were activated, and apoptosis was induced. Remarkably, activation of endoplasmic-reticulum (ER) stress induced by GSDMD promotes cell apoptosis during cisplatin chemotherapy, thereby increasing the treatment sensitivity of tumours. Therefore, for the first time, our work reveals an unreported nonpyroptotic function of the classic pyroptosis protein GSDMD: it promotes cell apoptosis during cisplatin chemotherapy by inducing eIF2α phosphorylation and ER stress, which are related to the drug sensitivity of tumours. Our study also indicated that GSDMD might serve as a biomarker for cisplatin sensitivity.

The fungi Eutypella could metabolize a myriad of natural products with unique structures and diverse bioactivities, which were deemed as key sources for lead compounds in drug discovery. Since the first research on the genus Eutypella in 2009, a myriad of secondary metabolites including terpenoids, alkaloids, and polyketides have been discovered in this genus, and most of them exhibited significant pharmacological activities. However, there are no systematic reviews that reported about the structures and bioactivities of Eutypella up to now. In this review, a total of 153 secondary metabolites and 42 references have been systematically summarized, and we found that the terpenoids (68.09%) and alkaloids (19.15%) were the new main components of this fungi, and the primary antiproliferative activity (64.89%) was mainly derived from the terpenoids and alkaloids. Thus, this review about the chemical diversity and biological activities of the metabolites from the fungus Eutypella provided a new perspective for the development of new drugs for pharmacologists.

Detecting circulating tumor cells (CTCs) from the peripheral blood of cancer patients is a promising approach for diagnosing early‐stage cancers, monitoring disease progression, and prescribing personalized anticancer therapy. However, it is still challenging to achieve effective and cell‐friendly isolation of CTCs due to their scarcity, heterogeneity, and vulnerability. Herein, a novel multifunctional platform based on fluorescent‐magnetic Fe3O4/Rhm B@ZIF‐8‐pTA nanoparticles (FR@Z‐pTA NPs) is developed for efficient CTCs isolation. FR@Z‐pTA NPs not only capture more than 88% of rare cancer cells for both EpCAM‐positive cells (MCF‐7, HepG2) and EpCAM‐negative cells (MDA‐MB‐231, HeLa) but also effectively release the captured cells with high efficiency (>80%) and viabilities (>90%) under cell‐friendly pH/ATP stimuli. More importantly, FR@Z‐pTA NPs exhibit excellent resistance to nonspecific adhesion of white blood cells (WBCs) and high detection sensitivity toward cancer cells in the patients’ blood. The present multifunctional CTCs detection platform integrating high sensitivity, broad‐spectrum capture, in situ fluorescent identification and cell‐friendly release offers a good solution to address current challenges of CTCs isolation from clinical blood samples.

Abstract Selective conversion of specific functional groups to desired products is highly important but still challenging in industrial catalytic processes. The adsorption state of surface species is the key factor in modulating the conversion of functional groups, which is correspondingly determined by the uniformity of active sites. However, the non‐identical number of metal atoms, geometric shape, and morphology of conventional nanometer‐sized metal particles/clusters normally lead to the non‐uniform active sites with diverse geometric configurations and local coordination environments, which causes the distinct adsorption states of surface species. Hence, it is highly desired to modulate the homogeneity of the active sites so that the catalytic transformations can be better confined to the desired direction. In this review, the construction strategies and characterization techniques of the uniform active sites that are atomically dispersed on various supports are examined. In particular, their unique behavior in boosting the catalytic performance in various chemical transformations is discussed, including selective hydrogenation, selective oxidation, Suzuki coupling, and other catalytic reactions. In addition, the dynamic evolution of the active sites under reaction conditions and the industrial utilization of the single‐atom catalysts are highlighted. Finally, the current challenges and frontiers are identified, and the perspectives on this flourishing field is provided.

High-definition transcranial direct current stimulation (HD-tDCS) has been shown to modulate decision-making; however, the neurophysiological mechanisms underlying this effect remain unclear. To further explore the neurophysiological processes of decision-making modulated by HD-tDCS, health participants underwent ten anodal (n = 16)/sham (n = 17) HD-tDCS sessions targeting the left DLPFC. Iowa gambling task was performed simultaneously with electroencephalography (EEG) before and after HD-tDCS. Iowa gambling task performance, the P300 amplitude, and the power of theta oscillation as an index of decision-making were compared. Behavioral changes were found that showed anodal HD-tDCS could improve the decision-making function, in which participants could make more advantageous choices. The electrophysiological results showed that the P300 amplitude significantly increased in CZ, CPZ electrode placement site and theta oscillation power significantly activated in FCZ, CZ electrode placement site after anodal HD-tDCS. Significant positive correlations were observed between the changes in the percent use of negative feedback and the changes in theta oscillation power before and after anodal HD-tDCS. This study showed that HD-tDCS is a promising technology in improving decision-making and theta oscillation induced by may be a predictor of improved decision-making.

Artificial intelligence (AI) has become one of the core driving forces for the future development of the medical industry, but patients are skeptical about the use of AI in medical care. Based on the intergroup threat theory (ITT), this study verified that patients would regard AI as an external group, triggering the perceived threat of the external group, which results in avoidance behaviors in the treatment (experiment 1: n = 446) and diagnosis (experiment 2: n = 330) scenarios. The results show that despite AI can provide expert-level accuracy in medical care, patients are still more likely to rely on human doctors and experience more negative emotions as AI is more involved in medical care (experiment 1). Furthermore, patients pay more attention to threats at the individual level related to themselves, such as realistic threats related to privacy issues and symbolic threats related to the neglect of personal characteristics. In contrast, realistic threats and symbolic threats at the group level had less effect on patients in the medical scenario (experiment 2).

Background: Telomerase reverse transcriptase promoter (TERT-p) mutation has been frequently found, but associated with contrary prognosis, in both low-grade gliomas and glioblastomas. For the low-grade gliomas (Grades II-III), TERT-p mutant patients have a better prognosis than the wildtype patients, whereas for the GBMs (Grade IV), TERT-p mutation is related to a poor prognosis. We hypothesize that there exist high-risk patients in LGGs who share GBM-like molecular features, including TERT-p mutation, and need more intensive treatment than other LGGs. A molecular signature is needed to identify these high-risk patients for an accurate and timely treatment.Methods: Using the within-sample relative expression orderings of gene pairs, we identified the gene pairs with significantly stable REOs, respectively, in both the TERT-p mutant LGGs and GBMs but with opposite directions in the two groups. These reversely stable gene pairs were used as the molecular signature to stratify the LGGs into high-risk and low-risk groups.Results: A signature consisting of 21 gene pairs was developed, which can classify LGGs into two groups with significantly different overall survival. The high-risk group has a similar genetic mutation profile and a similar survival profile as GBMs, and these high-risk tumors may progress to a more malignant state.Conclusion: The 21 gene-pair signature based on REOs is capable of identifying high-risk patients in LGGs and guiding the clinical choice for appropriate and timely intervention.

In this work, low voltage RF power capability on AlGaN/GaN and InAlN/GaN HEMTs is analyzed from the perspective of DC and pulse characteristics, for terminal applications whose operating voltage is usually in the range of 3 to 15 V. Device fabrication is performed on mature AlGaN/GaN heterojunction as well as strongly polarized InAlN/GaN heterojunction, to make a comparison of low voltage RF power capability between two devices. Although it suffers from relatively severe RF dispersion, InAlN/GaN HEMT delivers higher output power density (Pout) than its opponent, benefiting from the lower parasitic resistance and knee voltage as well as higher output current density. At 8 GHz, Pout of 1.62 W/mm and 1.10 W/mm are achieved for InAlN/GaN and AlGaN/GaN HEMT, respectively, both of which are biased at class AB operation and Vds of 9 V. However, the tremendous degradation of power added efficiency (PAE) occurs as the higher drain voltage is applied on InAlN/GaN HEMT, as the result of the severe gate leakage. What is more, a higher PAE is more necessary than Pout for terminal applications. Either InAlN/GaN HEMT or AlGaN/GaN HEMT has its own specific voltage range to deliver higher PAE. Concretely, InAlN/GaN HEMT is more suitable to applications with operating voltage not exceeding 6 V, and AlGaN/GaN HEMT is preferred for ones with relatively higher voltage, accompanied by the decent PAE as high as 62% to 66% and moderate Pout to meet the demand of various low voltage terminal applications.

Abstract Background Pneumothorax (PTX) may cause a life-threatening medical emergency with cardio-respiratory collapse that requires immediate intervention and rapid treatment. The screening and diagnosis of pneumothorax usually rely on chest radiographs. However, the pneumothoraces in chest X-rays may be very subtle with highly variable in shape and overlapped with the ribs or clavicles, which are often difficult to identify. Our objective was to create a large chest X-ray dataset for pneumothorax with pixel-level annotation and to train an automatic segmentation and diagnosis framework to assist radiologists to identify pneumothorax accurately and timely. Methods In this study, an end-to-end deep learning framework is proposed for the segmentation and diagnosis of pneumothorax on chest X-rays, which incorporates a fully convolutional DenseNet (FC-DenseNet) with multi-scale module and spatial and channel squeezes and excitation (scSE) modules. To further improve the precision of boundary segmentation, we propose a spatial weighted cross-entropy loss function to penalize the target, background and contour pixels with different weights. Results This retrospective study are conducted on a total of eligible 11,051 front-view chest X-ray images (5566 cases of PTX and 5485 cases of Non-PTX). The experimental results show that the proposed algorithm outperforms the five state-of-the-art segmentation algorithms in terms of mean pixel-wise accuracy (MPA) with $$0.93\pm 0.13$$ 0.93 ± 0.13 and dice similarity coefficient (DSC) with $$0.92\pm 0.14$$ 0.92 ± 0.14 , and achieves competitive performance on diagnostic accuracy with 93.45% and $$F_1$$ F 1 -score with 92.97%. Conclusion This framework provides substantial improvements for the automatic segmentation and diagnosis of pneumothorax and is expected to become a clinical application tool to help radiologists to identify pneumothorax on chest X-rays.

Therapeutic antibodies play a crucial role in the treatment of various diseases. However, the success rate of antibody drug development is low partially because of unfavourable biophysical properties of antibody drug candidates such as the high aggregation tendency, which is mainly driven by hydrophobic interactions of antibody molecules. Therefore, early screening of the risk of hydrophobic interaction of antibody drug candidates is crucial. Experimental screening is laborious, time-consuming, and costly, warranting the development of efficient and high-throughput computational tools for prediction of hydrophobic interactions of therapeutic antibodies. In the present study, 131 antibodies with hydrophobic interaction experiment data were used to train a new support vector machine-based ensemble model, termed SSH2.0, to predict the hydrophobic interactions of antibodies. Feature selection was performed against CKSAAGP by using the graph-based algorithm MRMD2.0. Based on the antibody sequence, SSH2.0 achieved the sensitivity and accuracy of 100.00 and 83.97%, respectively. This approach eliminates the need of three-dimensional structure of antibodies and enables rapid screening of therapeutic antibody candidates in the early developmental stage, thereby saving time and cost. In addition, a web server was constructed that is freely available at http://i.uestc.edu.cn/SSH2/.

Abstract Background Autotetraploid Carassius auratus (4nRCC, 4n = 200, RRRR) was derived from the whole genome duplication of diploid red crucian carp (Carassius auratus red var.) (2nRCC, 2n = 100, RR). To investigate the genetic effects of tetraploidization, we analyzed DNA variation, epigenetic modification and gene expression changes in the Sox9a-Amh-Cyp19a1a regulatory cascade between 4nRCC and 2nRCC. Results We found that the Sox9a gene contained two variants in 2nRCC and four variants in 4nRCC. Compared with that in 2nRCC, DNA methylation in the promoter regions of the Amh and Cyp19a1a genes in 4nRCC was altered by single nucleotide polymorphism (SNP) mutations, which resulted in the insertions and deletions of CpG sites, and the methylation levels of the Sox9a, Amh and Cyp19a1a genes increased after tetraploidization. The gene expression level of the Sox9a-Amh-Cyp19a1a regulatory cascade was downregulated in 4nRCC compared with that in 2nRCC. Conclusion The above results demonstrate that tetraploidization leads to significant changes in the genome, epigenetic modification and gene expression in the Sox9a-Amh-Cyp19a1a regulatory cascade; these findings increase the extant knowledge regarding the effects of polyploidization.

On-street cruising by drivers impedes the effectiveness of road traffic conditions and increases energy consumption and environmental impact. Existing models of on-street cruising for parking mainly embody those intrinsic on-street parking factors and disregard the extrinsic impacts from off-street parking gaming factors. This research focused on both the intrinsic and extrinsic elements, especially gaming factors, of off-street parking, i.e., the price of off-street parking, the waiting time of off-street parking, and the difference in walking time between their parking lots to their destinations. On-street cruising for a parking model is reconstructed in this paper in consideration with the equilibrium cruising time, i.e., the maximum tolerable cruise time after evaluating the cost of on-street and off-street parking. Correlation analysis showed that the off-street parking gaming factors were all positively related with the maximum tolerable cruise time. A simulation model was further presented for on-street cruising for the parking model by the cellular automata approach with real-world data. Simulation experiments demonstrated that the average speed of vehicles on the street increases by 9.858 km/h, the average delay decreases by 44.934 s, and the price of on-street parking increases by 4.5 CNY/h. The proposed on-street cruising for parking model proved effective by decreasing the maximum tolerable cruising time to bring significant improvements in average speed, average delay, and on-street cruising vehicles in road traffic flow.

Prefabricated buildings and off-site construction are increasingly adopted in modern construction. As one of the most concerning environmental impacts, the embodied carbon emission of prefabricated buildings has been extensively investigated in recent years. Due to the various influencing factors of carbon quantification, such as building characteristics, quantification boundary, emission sources, and quantification methods, no consensus has been reached so far. The impacts of the influencing factors on carbon quantification remain unclear. To fill this gap, this paper provides a systematic review and meta-analysis to comprehensively evaluate the recent research concerning the quantification of the embodied carbon emission of prefabricated buildings. In total, 43 peer-reviewed articles (96 building cases) were screened and analyzed. Twelve influencing factors of embodied carbon quantification have been identified and analyzed to give rise to a synthesized conclusion. The results of the meta-analysis indicated that the embodied carbon emission of prefabricated buildings varied significantly from 26.6 to 1644.4 kgCO2e/m2 in the reviewed literature. The results showed that some of the quantification factors could significantly influence the quantification results, such as the building structure forms, level of prefabrication, type of greenhouse gas considered, and data sources, while some factors have a lesser impact on carbon quantification results, such as the function of the building, quantification methods adopted, quantification tools/software used, and carbon inventory databases applied. The findings of this research provide readers with an in-depth and critical understanding of the quantification of the embodied carbon emission of prefabricated buildings. Research gaps and suggestions for future research are also provided based on the results of this work.

Whole genome duplication events have occurred frequently during the course of vertebrate evolution. To better understand the influence of polyploidization on the fish genome, we herein used the autotetraploid Carassius auratus (4n = 200, RRRR) (4nRR) resulting from the whole genome duplication of Carassius auratus (2n = 100, RR) (RCC) to explore the genomic and epigenetic alterations after polyploidization. We subsequently performed analyses of full-length transcriptome dataset, amplified fragment length polymorphism (AFLP) and methylation sensitive amplification polymorphism (MSAP) on 4nRR and RCC. By matching the results of 4nRR and RCC isoforms with reference genome in full-length transcriptome dataset, 649 and 1,971 novel genes were found in the RCC and 4nRR full-length geneset, respectively. Compared to Carassius auratus and Megalobrama amblycephala, 4nRR presented 3,661 unexpressed genes and 2,743 expressed genes. Furthermore, GO enrichment analysis of expressed genes in 4nRR revealed that they were enriched in meiosis I, whereas KEGG enrichment analysis displayed that they were mainly enriched in proteasome. Using AFLP analysis, we noted that 32.61% of RCC fragments had disappeared, while 32.79% of new bands were uncovered in 4nRR. Concerning DNA methylation, 4nRR exhibited a lower level of global DNA methylation than RCC. Additionally, 60.31% of methylation patterns in 4nRR were altered compared to RCC. These observations indicated that transcriptome alterations, genomic changes and regulation of DNA methylation levels and patterns had occurred in the newly established autotetraploid genomes, suggesting that genetic and epigenetic alterations were influenced by autotetraploidization. In summary, this study provides valuable novel insights into vertebrate genome evolution and generates relevant information for fish breeding.

Lymphoma is a systemic malignancy, originating from the lymphatic system, which accounts for 3 to 4% of all tumors. There are two major subtypes of lymphoma, namely, diffuse large B-cell lymphoma (DLBCL) and Hodgkin’s lymphoma (HL). Elucidation of the pathogenesis of these two lymphoma types is crucial for the identification of potential therapeutic targets. Compared with the corresponding knowledge of other diseases, the understanding of the regulatory networks involved in DLBCL and HL is relatively deficient. To address this, we comprehensively analyzed the mRNAs, lncRNAs, and miRNAs that were differentially expressed between normal and tumor samples of DLBCL and HL. In addition, functional enrichment analysis of the differentially expressed mRNAs was performed. We constructed two specific ceRNA networks of DLBCL and HL. The pathways enriched by dysregulated mRNAs in DLBCL and HL were mainly involved in immune responses, transcription process, and metabolism process. The ceRNA network analysis revealed that 45 ceRNAs were shared between the two ceRNA networks, including five pivotal lncRNAs (MALAT1, CTBP1-AS, THUMPD3-AS, PSMA3-AS1, and NUTM2A-AS1). In addition, we proposed a DLBCL survival risk model based on a DLBCL-specific network constructed by Lasso regression analysis. The model, which is based on eight mRNAs, exhibited excellent performance in regard to predicting outcomes in DLBCL patients, with a p value of 0.0017 and AUC of 0.9783. In summary, although the molecular mechanisms underlying tumorigenesis in DLBCL and HL were quite different, the same pivotal lncRNAs acted as key regulators. Our findings identify novel potential prognostic and therapeutic targets for DLBCL and HL.

The autotetraploid fish (4n = 200, RRRR) (abbreviated as 4nRR) resulted from the whole genome duplication of red crucian carp (Carassius auratus red var., 2n = 100, RR) (abbreviated as RCC). During investigation of the influence of polyploidization on organization and evolution of the multigene family of 5S rDNA, molecular organization and chromosomal localization of the 5S rDNA were characterized in autotetraploid fish. By sequence analysis of the coding region (5S) and adjacent non-transcribed spacer (NTS), three distinct 5S rDNA units (type I: 203 bp; type II: 340 bp; and type III: 477bp) were identified and characterized in 4nRR. These 5S rDNA units were inherited from their female parent (RCC), in which obvious base variations in NTS and array recombination of repeat units were found. Using fluorescence in situ hybridization employing different 5S rDNA units as probes, these 5S rDNA clusters were localized in chromosomes of 4nRR, respectively, and showed obvious loss of chromosomal loci (type I and type II). Our data revealed genetic variation of the 5S rDNA multigene family in the genome of autopolyploid fish. Furthermore, results provided new insights into the evolutionary patterns of this vertebrate multigene family.