A Deep-Learning Enabled Automatic Fetal Thalamus Diameter Measurement Algorithm.

The analysis of maternal factors that impact the normal development of the fetal thalamus is an emerging field of research and requires the retrospective measurement of fetal thalamus diameter (FTD). Unfortunately, FTD is not measured in routine 2D ultrasound (2D-US) screenings of fetuses. Manual measurement of FTD is a laborious, difficult, and error-prone process because the thalamus lacks well-defined boundaries in 2D-US images of the fetal brain as it has a similar echogenicity to the surrounding brain tissue. Traditional methods based on statistical shape models (SSMs) perform poorly in measuring FTD due to the noisy textures and fuzzy edges of the fetal thalamus in 2D-US images of the fetal brain. To overcome these difficulties, we propose a deep learning-based automatic FTD measurement algorithm, FTDNet. FTDNet measures FTD by learning to directly detect the measurement landmarks through supervised learning. The algorithm first detects the region of the brain that contains the thalamus structure, and then focuses on processing that region for FTD landmark detection. Our FTD dataset, developed through a consensus between two ultrasonographers, contains 1,111 pairs of landmark coordinates for measuring FTD and verified bounding boxes surrounding the fetal thalamus. To assess FTDNet's measurement consistency compared to the ground truth, we used the intraclass correlation coefficient (ICC). FTDNet achieved an ICC score of 0.734, significantly outperforming the prior SSM method and other baseline comparison methods. Our findings are an important step forward in understanding the maternal factors which influence fetal brain development.Clinical relevance- This work proposes an end-to-end thalamus detection and measurement algorithm for measuring fetal thalamus diameter. Our work represents a significant step in the research of how maternal factors can impact fetal thalamus development. The development of an automatic and accurate method for measuring FTD through deep learning has the potential to greatly advance this field of study.

Design, Synthesis, and Antitumor Activity Evaluation of 2-Arylmethoxy-4-(2,2'-dihalogen-substituted biphenyl-3-ylmethoxy) Benzylamine Derivatives as Potent PD-1/PD-L1 Inhibitors.

Novel 2-arylmethoxy-4-(2,2'-dihalogen-substituted biphenyl-3-ylmethoxy) benzylamine derivatives were designed, synthesized, and evaluated in vitro and in vivo against cancers as PD-1/PD-L1 inhibitors. Through the computer-aided structural optimization and the homogeneous time-resolved fluorescence (HTRF) assay, compound A56 was found to most strongly block the PD-1/PD-L1 interaction with an IC50 value of 2.4 ± 0.8 nM and showed the most potent activity. 1H NMR titration results indicated that A56 can tightly bind to the PD-L1 protein with KD < 1 µM. The X-ray diffraction data for the cocrystal structure of the A56/PD-L1 complex (3.5 Å) deciphered a novel binding mode in detail, which can account for its most potent inhibitory activity. Cell-based assays further demonstrated the strong ability of A56 as an hPD-1/hPD-L1 blocker. Especially in an hPD-L1 MC38 humanized mouse model, A56 significantly inhibited tumor growth without obvious toxicity, with a TGI rate of 55.20% (50 mg/kg, i.g.). In conclusion, A56 is a promising clinical candidate worthy of further development.

PD-L1 dimerisation induced by biphenyl derivatives mediates anti-breast cancer activity via the non-immune PD-L1-AKT-mTOR/Bcl2 pathway.

Recent studies on biphenyl-containing compounds, a type of PD-1/PD-L1 blocker which binds to PD-L1 and induces dimerisation, have focussed on its immune function. Herein, 10 novel biphenyl derivatives were designed and synthesised. The results of the CCK-8 showed that compounds have different anti-tumour activities for tumour cells in the absence of T cells. Particularly, 12j-4 can significantly induce the apoptosis of MDA-MB-231 cells (IC50 = 2.68 ± 0.27 µM). In further studies, 12j-4 has been shown to prevent the phosphorylation of AKT by binding to cytoplasmic PD-L1, which induces apoptosis in MDA-MB-231 cells through non-immune pathways. The inhibition of AKT phosphorylation restores the activity of GSK-3ß, ultimately resulting in the degradation of PD-L1. Besides, in vivo study indicated that 12j-4 repressed tumour growth in nude mice. As these biphenyls exert their anti-tumour effects mainly through non-immune pathways, they are worthy of further study as PD-L1 inhibitors.

Properties and mechanism of Cr(VI) removal by a ZnCl2-modified sugarcane bagasse biochar-supported nanoscale iron sulfide composite.

A ZnCl2-modified biochar-supported nanoscale iron sulfide composite (FeS-ZnBC) was successfully prepared to address the easy oxidization of FeS and enhance Cr(VI) removal from water. The material was characterized by SEM, XRD, FTIR, and XPS. The effects of FeS:ZnBC mass ratio, FeS-ZnBC dosage, solution pH, initial Cr(VI) concentration, and reaction time on the adsorption performance were investigated. The results revealed that the optimum adsorption capacity of FeS-ZnBC (FeS:ZnBC = 1:2) for Cr(VI) was 264.03 mg/g at 298 K (pH = 2). A Box-Behnken design (BBD) was applied to optimize the input variables that affected the adsorption of Cr(VI) solution. The results revealed that the highest removal (99.52%) of Cr(VI) solution was achieved with a Cr(VI) initial concentration of 150.59 mg/L, FeS-ZnBC adsorbent dosage of 2 g/L, and solution pH of 2. The sorption kinetics could be interpreted using a pseudo-second-order kinetic model. The isotherms were simulated using the Redlich-Peterson isotherm model, indicating that Cr(VI) removal by the FeS-ZnBC composites was a hybrid chemical reaction-sorption process. The main mechanisms of Cr(VI) removal by FeS-ZnBC were adsorption, chemical reduction, and complexation. This study demonstrated that FeS-ZnBC has potential application prospects in Cr(VI) removal.

Dual Gas-responsive Fluorescent Diblock Copolymer Synthesized via RAFT Polymerization.

Stimulus-responsive polymers with luminescence properties have a wide range of applications in the fields of controlled drug release, fluorescent probes, and biological stents. In this paper, carbon dioxide (CO2)/oxygen (O2) dual-responsive fluorescent diblock copolymers were synthesized by the reversible addition-fragmentation chain transfer (RAFT) polymerization method with two fluorescent monomers synthesized as its luminescence source, DEAEMA (CO2 responsive monomer) and tFMA (O2 responsive monomer). An experimental study demonstrated that the synthesized stimulus-responsive fluorescent polymer had a high sensitivity to CO2; the double-responsive fluorescent diblock copolymer could form and achieve the reversal of polymer micelles in the aqueous solution when it was sequentially subjected to the introduction of CO2 and O2.

Predicting Pseudogene-miRNA Associations Based on Feature Fusion and Graph Auto-Encoder.

Pseudogenes were originally regarded as non-functional components scattered in the genome during evolution. Recent studies have shown that pseudogenes can be transcribed into long non-coding RNA and play a key role at multiple functional levels in different physiological and pathological processes. microRNAs (miRNAs) are a type of non-coding RNA, which plays important regulatory roles in cells. Numerous studies have shown that pseudogenes and miRNAs have interactions and form a ceRNA network with mRNA to regulate biological processes and involve diseases. Exploring the associations of pseudogenes and miRNAs will facilitate the clinical diagnosis of some diseases. Here, we propose a prediction model PMGAE (Pseudogene-MiRNA association prediction based on the Graph Auto-Encoder), which incorporates feature fusion, graph auto-encoder (GAE), and eXtreme Gradient Boosting (XGBoost). First, we calculated three types of similarities including Jaccard similarity, cosine similarity, and Pearson similarity between nodes based on the biological characteristics of pseudogenes and miRNAs. Subsequently, we fused the above similarities to construct a similarity profile as the initial representation features for nodes. Then, we aggregated the similarity profiles and associations of nodes to obtain the low-dimensional representation vector of nodes through a GAE. In the last step, we fed these representation vectors into an XGBoost classifier to predict new pseudogene-miRNA associations (PMAs). The results of five-fold cross validation show that PMGAE achieves a mean AUC of 0.8634 and mean AUPR of 0.8966. Case studies further substantiated the reliability of PMGAE for mining PMAs and the study of endogenous RNA networks in relation to diseases.

HHQ-4, a quinoline derivate, preferentially inhibits proliferation of glucose-deprived breast cancer cells as a GRP78 down-regulator.

As a central regulator for endoplasmic reticulum (ER) stress, glucose-regulated protein 78 (GRP78), controls the activation of ER-transmembrane signaling mechanisms by inducing unfolded protein response (UPR) in response to ER stress. Although limited glucose availability often occurs in poorly vascularized solid cancers, cancer cells often initiate the UPR to support cellular homeostasis and survival under stress conditions. Therefore, targeting GRP78 expression and UPR pathway activation may provide a new strategy for anticancer therapy. Based on this premise, we investigated the molecular mechanisms of a synthetic quinolone derivative, 2-hexyl-3-methyl-4(1H)-quinolinone (HHQ-4), in regulating the GRP78 expression and UPR transcriptional program under glucose deprivation or 2-deoxy-d-glucose (2-DG)-stressed conditions. We found that HHQ-4 suppressed the transcriptional and translational expression of GRP78 gene in glucose-deprived breast cancer cells. HHQ-4 also showed selective antiproliferative activity against glucose-deprived breast cancer cells. Constitutive expression of GRP78 completely prevented breast cancer cells from HHQ-4-mediated proliferation inhibition during glucose starvation, stressing the important role of suppression of the GRP78 in HHQ-4-mediated cell proliferation inhibition. HHQ-4 was also found to exert inhibitory activity against breast cancer cell proliferation by suppressing three survival arms of the UPR, including PERK/eIF2α/ATF4, IRE1/XBP1, and ATF6, which orchestrate an intricate signaling network to modulate GRP78 gene transcription under glucose-deprived stress. Furthermore, HHQ-4 combined with 2-DG synergistically inhibited breast cancer cell proliferation. Our findings show HHQ-4 could be a promising candidate, alone or in combination with 2-DG, for selectively inhibiting breast cancer cell proliferation by down-regulating the transcription and expression of GRP78 under stressful microenvironments.

Genetic cause for congenital methemoglobinemia in an Australian Pomeranian dog.

Little is known about genetic causes of congenital methemoglobinemia in dogs. Here, we report a CYB5 R3 mutation in a Pomeranian dog with congenital methemoglobinemia. A 6-year-old neutered female Pomeranian dog was investigated for cyanosis noticed during anesthesia for an orthopedic procedure. The history included lifelong mild exercise intolerance and bluish tongue. Methemoglobinemia was diagnosed using co-oximetry. The CYB5 R3 gene was analyzed by comparing the patient's genomic DNA with the reference canine sequence. Mutation functional significance was investigated using snpEff and multispecies protein homology analyses. A homozygous missense single nucleotide CYB5 R3 mutation (ATC ➔ CTC at codon 194) caused a p.Ile194Leu substitution. The pIle194 residue is highly conserved in other mammals, supporting the likely pathogenicity of the substitution. The mutation described here is identical to that associated with familial methemoglobinemia in a family of Japanese Pomeranian dogs. This observation, together with the homozygous mutation found in our case, indicates that the mutant allele may be widespread within the Pomeranian breed internationally.