Weakly supervised low-dose computed tomography denoising based on generative adversarial networks.

Background: Low-dose computed tomography (LDCT) is a diagnostic imaging technique designed to minimize radiation exposure to the patient. However, this reduction in radiation may compromise computed tomography (CT) image quality, adversely impacting clinical diagnoses. Various advanced LDCT methods have emerged to mitigate this challenge, relying on well-matched LDCT and normal-dose CT (NDCT) image pairs for training. Nevertheless, these methods often face difficulties in distinguishing image details from nonuniformly distributed noise, limiting their denoising efficacy. Additionally, acquiring suitably paired datasets in the medical domain poses challenges, further constraining their applicability. Hence, the objective of this study was to develop an innovative denoising framework for LDCT images employing unpaired data. Methods: In this paper, we propose a LDCT denoising network (DNCNN) that alleviates the need for aligning LDCT and NDCT images. Our approach employs generative adversarial networks (GANs) to learn and model the noise present in LDCT images, establishing a mapping from the pseudo-LDCT to the actual NDCT domain without the need for paired CT images. Results: Within the domain of weakly supervised methods, our proposed model exhibited superior objective metrics on the simulated dataset when compared to CycleGAN and selective kernel-based cycle-consistent GAN (SKFCycleGAN): the peak signal-to-noise ratio (PSNR) was 43.9441, the structural similarity index measure (SSIM) was 0.9660, and the visual information fidelity (VIF) was 0.7707. In the clinical dataset, we conducted a visual effect analysis by observing various tissues through different observation windows. Our proposed method achieved a no-reference structural sharpness (NRSS) value of 0.6171, which was closest to that of the NDCT images (NRSS =0.6049), demonstrating its superiority over other denoising techniques in preserving details, maintaining structural integrity, and enhancing edge contrast. Conclusions: Through extensive experiments on both simulated and clinical datasets, we demonstrated the superior efficacy of our proposed method in terms of denoising quality and quantity. Our method exhibits superiority over both supervised techniques, including block-matching and 3D filtering (BM3D), residual encoder-decoder convolutional neural network (RED-CNN), and Wasserstein generative adversarial network-VGG (WGAN-VGG), and over weakly supervised approaches, including CycleGAN and SKFCycleGAN.

Swollen Necrotic Lymphadenitis Infected with Mycobacterium Paracondontium in an AIDS Patient: a Case Report and Literature Review.

Background: Non-tuberculous mycobacteria (NTM) are a group of mycobacteria that are commonly found in the environment and can cause disease in humans. The symptoms of NTM infection can be similar to those of tuberculosis, making diagnosis challenging. The morbidity associated with NTM is increasing, and clinical management can be challenging. Case Description: This report details the case of a 32-year-old male who was found to have multiple enlarged and partially necrotic lymph nodes in the neck, axilla, mediastinum, and retroperitoneum. The causative agent was rapidly identified as Mycobacterium paracondontium through pathogen-targeted sequencing (tNGS). After two weeks of treatment with azithromycin, moxifloxacin, rifabutin, and amikacin, the patient's uncomfortable symptoms had resolved, and he is currently undergoing further review. Conclusion: It is imperative that clinicians remain vigilant for the presence of NTM, particularly those that are rare, given their pervasiveness in the environment. Prompt diagnosis is of paramount importance, and molecular identification techniques represent a crucial tool in this regard. In vitro drug sensitivity testing should be conducted whenever feasible to guarantee the administration of an efficacious treatment regimen.

High-performance electrolyte-gated amorphous InGaZnO field-effect transistor for label-free DNA sensing.

Accurate, convenient, label-free, and cost-effective biomolecules detection platforms are currently in high demand. In this study, we showcased the utilization of electrolyte-gated InGaZnO field-effect transistors (IGZO FETs) featuring a large on-off current ratio of over 106 and a low subthreshold slope of 78.5 mV/dec. In the DNA biosensor, the modification of target DNA changed the effective gate voltage of IGZO FETs, enabling an impressive low detection limit of 0.1 pM and a wide linear detection range from 0.1 pM to 1 µM. This label-free detection method also exhibits high selectivity, allowing for the discrimination of single-base mismatch. Furthermore, the reuse of gate electrodes and channel films offers cost-saving benefits and simplifies device fabrication processes. The electrolyte-gated IGZO FET biosensor presented in this study shows great promise for achieving low-cost and highly sensitive detection of various biomolecules.

The Chrysosplenium sinicum genome provides insights into adaptive evolution of shade plants.

Chrysosplenium sinicum, a traditional Tibetan medicinal plant, can successfully thrive in low-light environments for long periods of time. To investigate the adaptive evolution of shade plants in low-light environments, we generated a chromosome-scale genome assembly (~320 Mb) for C. sinicum by combining PacBio sequencing and Hi-C technologies. Based on our results, gene families related to photosynthesis and cell respiration greatly expanded and evolved in C. sinicum genome due to intracellular DNA transfer from organelle genome to nuclear genome. Under positive selective pressure, adaptive evolution of light-harvesting complex II (LHCII) component protein CsLhcb1s resulted in the expansion of threonine residues at the phosphorylation site of STN7 kinase, potentially establishing a crucial genomic foundation for enhancing C. sinicum's adaptability in low-light environments. Through transcriptome and metabolome analysis, we identified chrysosplenol and chrysosplenoside as predominant flavonoid metabolites of C. sinicum and predicted their synthesis pathways. In addition, analysis of alternative splicing (AS) revealed that AS events help regulate state transition and flavonoid biosynthesis. The present study provides new insights into the genomes of shade plants exposed to low-light conditions and adaptive evolution of these genomes; in addition, the results improve our current knowledge on the biosynthetic and regulatory processes of chrysosplenol and chrysosplenoside.

Discovery of novel pyrazolo[1,5-a]pyrimidine derivatives as potent reversal agents against ABCB1-mediated multidrug resistance.

The P-glycoprotein (ABCB1)-mediated multidrug resistance (MDR) has emerged as a significant impediment to the efficacy of cancer chemotherapy in clinical therapy, which could promote the development of effective agents for MDR reversal. In this work, we reported the exploration of novel pyrazolo [1,5-a]pyrimidine derivatives as potent reversal agents capable of enhancing the sensitivity of ABCB1-mediated MDR MCF-7/ADR cells to paclitaxel (PTX). Among them, compound 16q remarkably increased the sensitivity of MCF-7/ADR cells to PTX at 5 µM (IC50 = 27.00 nM, RF = 247.40) and 10 µM (IC50 = 10.07 nM, RF = 663.44). Compound 16q could effectively bind and stabilize ABCB1, and does not affect the expression and subcellular localization of ABCB1 in MCF-7/ADR cells. Compound 16q inhibited the function of ABCB1, thereby increasing PTX accumulation, and interrupting the accumulation and efflux of the ABCB1-mediated Rh123, thus resulting in exhibiting good reversal effects. In addition, due to the potent reversal effects of compound 16q, the abilities of PTX to inhibit tubulin depolymerization, and induce cell cycle arrest and apoptosis in MCF-7/ADR cells under low-dose conditions were restored. These results indicate that compound 16q might be a promising potent reversal agent capable of revising ABCB1-mediated MDR, and pyrazolo [1,5-a]pyrimidine might represent a novel scaffold for the discovery of new ABCB1-mediated MDR reversal agents.

Prevalence and genotype distribution of human papillomavirus infection among 66000 women from 2014 to 2023 in the plateau region of Southwest China.

BACKGROUND: Persistent infection with high-risk human papillomavirus (HR-HPV) plays a key role in the onset of cervical cancer. This study was designed to examine the epidemiological trends and genotype distribution of HPV from 2014 to 2023 in the plateau region of Southwest China. METHODS: The findings could offer valuable insights for clinical screening of cervical cancer and the formulation of HPV vaccination policies. This retrospective study analyzed 66,000 women who received HPV-DNA testing at the First People's Hospital of Qujing, Yunnan, China, between 2014 and 2023. The cohort consisted of 33,512 outpatients, 3,816 inpatients, and 28,672 individuals undergoing health examinations. Cervical cells were collected for DNA extraction, and PCR amplification along with Luminex xMAP technology were used to detect 27 HPV genotypes. The data analysis was conducted using GraphPad Prism and IBM SPSS Statistics 27 software. RESULTS: The overall HPV infection rate at the First People's Hospital of Qujing declined from 24.92% in 2014 to 16.29% in 2023, averaging 16.02%. Specific infection rates were 18.50% among outpatients, 12.97% among inpatients, and 13.53% for health examination attendees. The predominant high-risk HPV genotypes identified were HPV52 (2.61%), HPV16 (2.06%), HPV58 (1.81%), HPV53 (1.55%), and HPV39 (1.09%). Meanwhile, the most frequent low-risk HPV genotypes were HPV6 (1.30%), HPV61 (1.21%), and HPV11 (0.85%). In HPV-positive cases, the distribution of single, double, triple, and quadruple or more infections were 79.90%, 15.17%, 3.59%, and 1.33%, respectively. The proportions of pure LR-HPV, pure HR-HPV, and mixed infections were 22.16%, 67.82%, and 10.02%, respectively. Age-specific analysis revealed a bimodal distribution of HPV infection, with the infection rate rapidly decreasing from 44.02% in the ≤ 19 age group to 19.55% in the 20-29 age group and 13.84% in the 30-39 age group, followed by a gradual increase to 14.64% in the 40-49 age group, 16.65% in the 50-59 age group, and 22.98% in the ≥ 60 age group. The coverage rates of the three available vaccines are all below 50%. The results of this study indicated a declining trend in HPV prevalence in the plateau region of Southwest China over the period from 2014 to 2023, especially in the reduction of genotypes targeted by vaccines. CONCLUSION: There were significant variations in the genotypes prevalent among different age groups, years, and patient sources within the same region. The underwhelming vaccination rates emphasize the critical need for developing either a multivalent vaccine or a personalized vaccine that targets the HPV genotypes common in the Chinese population. Furthermore, vaccinating adolescents to curb HPV infection and ensuring regular cervical cancer screenings for postmenopausal women are crucial steps.

Association between metabolic score for insulin resistance and regression to normoglycemia from prediabetes in Chinese adults: A retrospective cohort study.

BACKGROUND: Metabolic score for insulin resistance (METS-IR) is a surrogate index to estimate insulin sensitivity. The aim of this study was to examine the association between METS-IR and regression to normoglycemia in Chinese adults with prediabetes. METHODS: A total of 15,415 Chinese adults with prediabetes defined by their fasting blood glucose were included in this retrospective study. The association between METS-IR and regression to normoglycemia from prediabetes was evaluated using the Cox proportional hazards regression model. A Cox proportional hazards regression with cubic spline function was performed to explore the nonlinear association between METS-IR and regression to normoglycemia. Kaplan-Meier curves was used to describe the probability of regression to normoglycemia from prediabetes. RESULTS: In multivariate Cox proportional hazards regression analyses, the increase in METS-IR was independently associated with a reduced probability of regression to normoglycemia from prediabetes (all p < 0.01 in models 1-3). A nonlinear association between METS-IR and the probability of regression to normoglycemia was observed, with an inflection point of 49.3. The hazard ratio on the left side of the inflection point was 0.965 (95% CI 0.953-0.976). Subgroup analyses demonstrated the robustness of our findings. CONCLUSION: This study demonstrated a negative and nonlinear association between METS-IR and regression to normoglycemia in Chinese adults with prediabetes. When METS-IR is below 49.3, reducing METS-IR could significantly increase the probability of regression to normoglycemia from prediabetes.

Etiologies of Persistent Aminotransferase Elevations in Chronic Hepatitis B Patients Treated with Nucleos(t)ide Analogs.

Background/Aims: Recent studies revealed that patients with persistent aminotransferase elevations after antiviral treatment had higher risk of hepatic events; yet its underlying causes remain unclear. Our study aimed to investigate the etiologies of persistent aminotransferase elevations in patients treated with nucleos(t)ide analogs (NAs). Materials and Methods: A retrospective study was conducted on chronic hepatitis B (CHB) patients who had been receiving NA treatment for over a year and had an aminotransferase level greater than 40 IU/mL (more than twice, with a 3-month interval) and subsequently underwent a liver biopsy. Results: The study group included 46 patients (34 males) with a mean age of 44.8 ± 20.3 years (range: 24-71 years).The average dura- tion of NA therapy was 3.7 years (1.1-10.6 years). The etiologies of persistant transaminase elevation were categorized into 4 groups: patients with low hepatitis B virus (HBV) viral load (LVL, n = 11); concurrent non-alcoholic fatty liver disease (NAFLD, n = 12); concurrent other liver diseases (OLD, n = 12); and unknown liver dysfunction (ULD, n = 11). The proportion of G ≥ 2 inflammation was significantly higher in the LVL group (90.9%) compared to NAFLD (33.3%), OLD (50%), and ULD (27.2%) groups (P = .012). The hepatitis B e-antigen (HBeAg)-positive group exhibited a younger age (34.5 ± 10.2 vs. 48.1 ± 9.4 years, P < .001), a lower proportion of fibrosis F ≥ 2 (36.3% vs. 77.1%, P = .012), and a higher prevalence of detectable HBV DNA (54.5% vs.14.2%, P = .00632) compared to the HBeAg-negative group. Conclusion: The etiology of persistent aminotransferase elevations in CHB patients undergoing NAs treatment warrants investigation. Besides the commonly observed NAFLD and low HBV viral load, concurrent presence of other liver diseases requires elucidation.The proportion of G≥2 inflammation was higher in the LVL group.

Development of a 2A peptide-based multigene expression system and its application for enhanced production of ganoderic acids in Ganoderma lucidum.

Ganoderma has received much attention for its medicinal value, but the manipulation of multiple genes remains a challenge, hindering the genetic engineering of this species for the development of cell factories. Here, we first showed that the presence of an intron is necessary for the efficient expression of the endogenous cDNA of carboxin-resistant gene (cbx) in G. lucidum. Then, the self-cleaving function of 2 A peptide was investigated in G. lucidum by linking cbx cDNA to the codon-optimized hygromycin B-resistant gene (ophph) using the 2A-peptide sequence. The results showed that cbx cDNA and ophph can be successfully expressed in G. lucidum in a bicistronic manner from a single transcript. Moreover, the expression of both genes was not affected by the order within the 2 A cassette. In addition, simultaneous expression of cbx cDNA, ophph, and codon-optimized yellow fluorescent protein gene (opyfp) was conducted for the first time in G. lucidum using the 2 A peptide-based approach. The developed method was successfully applied to express both cDNA of the 3-hydroxy-3-methylglutaryl coenzyme A reductase (hmgr) and squalene epoxidase gene (se) for enhanced production of ganoderic acids (GAs) in G. lucidum. The engineered strain produced the maximum content of GA-Mk, GA-T, GA-S, and GA-Me were 26.56±3.53,39.58±3.75, 16.54±2.16, and 19.1±1.87 µg/100 mg dry weight, respectively. These values were 3.85-, 4.74-, 3.65-, and 3.23-fold higher than those produced by the control strain. The developed method will be useful for the manipulation of complex metabolic or regulatory pathways involving multiple genes in Ganoderma.

Inflammatory Trajectory and Anti-Inflammatory Pharmacotherapy in Frozen Elephant Trunk-Treated Acute Type I Aortic Dissection.

Background: Acute DeBakey type I aortic dissection is associated with high morbidity and mortality. Little is known regarding the role of leukocyte trajectory in prognosis. Methods: We included adult acute DeBakey type I aortic dissection patients with emergency frozen elephant trunk and total arch replacement in 2 cardiovascular centers (2020-2022). We used latent class mixed model to group patients according to their leukocyte patterns from hospital admission to the first 5 days after surgery. We investigated the association of leukocyte trajectory and 30-day and latest follow-up mortality (October 31, 2023), exploratorily analyzing the effects of ulinastatin treatment on outcome. Results: Of 255 patients included, 3 distinct leukocyte trajectories were identified: 196 in group I (decreasing trajectory), 34 in group II (stable trajectory), and 25 in group III (rising trajectory). Overall, 30-day mortality was 25 (9.8%), ranging from 8.2% (16/196) in group I, 8.8% (3/34) in group II, to 24.0% (6/25) in group III (P for trend = .036). Group III was associated with higher mortality both at 30 days (adjusted hazard ratio, 3.260; 95% CI, 1.071-9.919; P = .037) and at the last follow-up (adjusted hazard ratio, 2.840; 95% CI, 1.098-7.345; P = .031) compared with group I. Conclusions: Distinct and clinically relevant groups can be identified by analyzing leukocyte trajectories, and a rising trajectory was associated with higher short-term and midterm mortality.

Clinical efficacy of laparoscopic cholecystectomy plus cholangioscopy for the treatment of cholecystolithiasis combined with choledocholithiasis.

BACKGROUND: Currently, endoscopic retrograde cholangiopancreatography (ERCP) plus laparoscopic cholecystectomy (LC) is the main treatment for cholecystolithiasis combined with choledocholithiasis. However, the treatment is unsatisfactory, and the development of better therapies is needed. AIM: To determine the clinical efficacy of LC plus cholangioscopy for cholecystolithiasis combined with choledocholithiasis. METHODS: Patients (n = 243) with cholecystolithiasis and choledocholithiasis admitted to The Affiliated Haixia Hospital of Huaqiao University (910th Hospital of Joint Logistic Support Force) between January 2019 and December 2023 were included in the study; 111 patients (control group) underwent ERCP + LC and 132 patients (observation group) underwent LC + laparoscopic common bile duct exploration (LCBDE). Surgical success rates, residual stone rates, complications (pancreatitis, hyperamylasemia, biliary tract infection, and bile leakage), surgical indicators [intraoperative blood loss (IBL) and operation time (OT)], recovery indices (postoperative exhaust/defecation time and hospital stay), and serum inflammatory markers [C-reactive protein (CRP), tumor necrosis factor-α (TNF-α), and interleukin-6 (IL-6) were compared. RESULTS: No significant differences in surgical success rates and residual stone rates were detected between the observation and control groups. However, the complication rate, IBL, OT, postoperative exhaust/defecation time, and hospital stays were significantly reduced in the observation group compared with the control group. Furthermore, CRP, TNF-α, and IL-6 Levels after treatment were reduced in the observation group compared with the levels in the control group. CONCLUSION: These results indicate that LC + LCBDE is safer than ERCP + LC for the treatment of cholecystolithiasis combined with choledocholithiasis. The surgical risks and postoperative complications were lower in the observation group compared with the control group. Thus, patients may recover quickly with less inflammation after LCBDE.

Diagnostic significance of serum levels of serum amyloid A, procalcitonin, and high-mobility group box 1 in identifying necrotising enterocolitis in newborns.

BACKGROUND: Necrotising enterocolitis (NEC) is a critical gastrointestinal emergency affecting premature and low-birth-weight neonates. Serum amyloid A (SAA), procalcitonin (PCT), and high-mobility group box 1 (HMGB1) have emerged as potential biomarkers for NEC due to their roles in inflammatory response, tissue damage, and immune regulation. AIM: To evaluate the diagnostic value of SAA, PCT, and HMGB1 in the context of NEC in newborns. METHODS: The study retrospectively analysed the clinical data of 48 newborns diagnosed with NEC and 50 healthy newborns admitted to the hospital. Clinical, radiological, and laboratory findings, including serum SAA, PCT, and HMGB1 Levels, were collected, and specific detection methods were used. The diagnostic value of the biomarkers was evaluated through statistical analysis, which was performed using chi-square test, t-test, correlation analysis, and receiver operating characteristic (ROC) analysis. RESULTS: The study demonstrated significantly elevated levels of serum SAA, PCT, and HMGB1 Levels in newborns diagnosed with NEC compared with healthy controls. The correlation analysis indicated strong positive correlations among serum SAA, PCT, and HMGB1 Levels and the presence of NEC. ROC analysis revealed promising sensitivity and specificity for serum SAA, PCT, and HMGB1 Levels as potential diagnostic markers. The combined model of the three biomarkers demonstrating an extremely high area under the curve (0.908). CONCLUSION: The diagnostic value of serum SAA, PCT, and HMGB1 Levels in NEC was highlighted. These biomarkers potentially improve the early detection, risk stratification, and clinical management of critical conditions. The findings suggest that these biomarkers may aid in timely intervention and the enhancement of outcomes for neonates affected by NEC.

Advanced electrochemical membrane technologies for near-complete resource recovery and zero-discharge of urine: Performance optimization and evaluation.

The depletion of nutrient sources in fertilizers demands a paradigm shift in the treatment of nutrient-rich wastewater, such as urine, to enable efficient resource recovery and high-value conversion. This study presented an integrated bipolar membrane electrodialysis (BMED) and hollow fiber membrane (HFM) system for near-complete resource recovery and zero-discharge from urine treatment. Computational simulations and experimental validations demonstrated that a higher voltage (20 V) significantly enhanced energy utilization, while an optimal flow rate of 0.4 L/min effectively mitigated the negative effects of concentration polarization and electro-osmosis on system performance. Within 40 min, the process separated 90.13% of the salts in urine, with an energy consumption of only 8.45 kWh/kgbase. Utilizing a multi-chamber structure for selective separation, the system achieved recovery efficiencies of 89% for nitrogen, 96% for phosphorus, and 95% for potassium from fresh urine, converting them into high-value products such as 85 mM acid, 69.5 mM base, and liquid fertilizer. According to techno-economic analysis, the cost of treating urine using this system at the lab-scale was $6.29/kg of products (including acid, base, and (NH4)2SO4), which was significantly lower than the $20.44/kg cost for the precipitation method to produce struvite. Excluding fixed costs, a net profit of $18.24/m3 was achieved through the recovery of valuable products from urine using this system. The pilot-scale assessment showed that the net benefit amounts to $19.90/m3 of urine, demonstrating significant economic feasibility. This study presents an effective approach for the near-complete resource recovery and zero-discharge treatment of urine, offering a practical solution for sustainable nutrient recycling and wastewater management.

The Formation Mechanism of Carbonized Polymer Dots: Crosslinking-Induced Nucleation and Carbonization.

Carbon dots (CDs), as a kind of zero-dimensional nanomaterials, have been widely synthesized by bottom-up methods from various precursors. However, the formation mechanism is still unclear and controversial, which also brings difficulty to the regulation of structures and properties. Only some tentative formation processes were postulated by analyzing the products obtained at different reaction times and temperatures. Here, the effect of crosslinking on the formation of carbonized polymer dots (CPDs) is explored. Crosslinking-induced nucleation and carbonization (CINC) is proposed as the driving force for the formation of CPDs. Under hydrothermal synthesis, the precursors are initiated to polymerize and crosslink. The crosslinking brings higher hydrophobicity to generate the hydrophilic/hydrophobic microphase separation, which promotes dehydration and carbonization resulting in the formation of CPDs. Based on the principle of CINC, the influence factors of size are also revealed. Moreover, the dissipative particle dynamics (DPD) simulation is employed to support this formation mechanism. This concept of CINC will bring light to the formation process of CPDs, as well as facilitate the regulation of CPDs' size and photoluminescence.

A 3D hierarchical cross-modality interaction network using transformers and convolutions for brain glioma segmentation in MR images.

BACKGROUND: Precise glioma segmentation from multi-parametric magnetic resonance (MR) images is essential for brain glioma diagnosis. However, due to the indistinct boundaries between tumor sub-regions and the heterogeneous appearances of gliomas in volumetric MR scans, designing a reliable and automated glioma segmentation method is still challenging. Although existing 3D Transformer-based or convolution-based segmentation networks have obtained promising results via multi-modal feature fusion strategies or contextual learning methods, they widely lack the capability of hierarchical interactions between different modalities and cannot effectively learn comprehensive feature representations related to all glioma sub-regions. PURPOSE: To overcome these problems, in this paper, we propose a 3D hierarchical cross-modality interaction network (HCMINet) using Transformers and convolutions for accurate multi-modal glioma segmentation, which leverages an effective hierarchical cross-modality interaction strategy to sufficiently learn modality-specific and modality-shared knowledge correlated to glioma sub-region segmentation from multi-parametric MR images. METHODS: In the HCMINet, we first design a hierarchical cross-modality interaction Transformer (HCMITrans) encoder to hierarchically encode and fuse heterogeneous multi-modal features by Transformer-based intra-modal embeddings and inter-modal interactions in multiple encoding stages, which effectively captures complex cross-modality correlations while modeling global contexts. Then, we collaborate an HCMITrans encoder with a modality-shared convolutional encoder to construct the dual-encoder architecture in the encoding stage, which can learn the abundant contextual information from global and local perspectives. Finally, in the decoding stage, we present a progressive hybrid context fusion (PHCF) decoder to progressively fuse local and global features extracted by the dual-encoder architecture, which utilizes the local-global context fusion (LGCF) module to efficiently alleviate the contextual discrepancy among the decoding features. RESULTS: Extensive experiments are conducted on two public and competitive glioma benchmark datasets, including the BraTS2020 dataset with 494 patients and the BraTS2021 dataset with 1251 patients. Results show that our proposed method outperforms existing Transformer-based and CNN-based methods using other multi-modal fusion strategies in our experiments. Specifically, the proposed HCMINet achieves state-of-the-art mean DSC values of 85.33% and 91.09% on the BraTS2020 online validation dataset and the BraTS2021 local testing dataset, respectively. CONCLUSIONS: Our proposed method can accurately and automatically segment glioma regions from multi-parametric MR images, which is beneficial for the quantitative analysis of brain gliomas and helpful for reducing the annotation burden of neuroradiologists.

A comprehensive review of new small molecule drugs approved by the FDA in 2022: Advance and prospect.

In 2022, the U.S. Food and Drug Administration approved a total of 16 marketing applications for small molecule drugs, which not only provided dominant scaffolds but also introduced novel mechanisms of action and clinical indications. The successful cases provide valuable information for optimizing efficacy and enhancing pharmacokinetic properties through strategies like macrocyclization, bioequivalent group utilization, prodrug synthesis, and conformation restriction. Therefore, gaining an in-depth understanding of the design principles and strategies underlying these drugs will greatly facilitate the development of new therapeutic agents. This review focuses on the research and development process of these newly approved small molecule drugs including drug design, structural modification, and improvement of pharmacokinetic properties to inspire future research in this field.

A 3D boundary-guided hybrid network with convolutions and Transformers for lung tumor segmentation in CT images.

-Accurate lung tumor segmentation from Computed Tomography (CT) scans is crucial for lung cancer diagnosis. Since the 2D methods lack the volumetric information of lung CT images, 3D convolution-based and Transformer-based methods have recently been applied in lung tumor segmentation tasks using CT imaging. However, most existing 3D methods cannot effectively collaborate the local patterns learned by convolutions with the global dependencies captured by Transformers, and widely ignore the important boundary information of lung tumors. To tackle these problems, we propose a 3D boundary-guided hybrid network using convolutions and Transformers for lung tumor segmentation, named BGHNet. In BGHNet, we first propose the Hybrid Local-Global Context Aggregation (HLGCA) module with parallel convolution and Transformer branches in the encoding phase. To aggregate local and global contexts in each branch of the HLGCA module, we not only design the Volumetric Cross-Stripe Window Transformer (VCSwin-Transformer) to build the Transformer branch with local inductive biases and large receptive fields, but also design the Volumetric Pyramid Convolution with transformer-based extensions (VPConvNeXt) to build the convolution branch with multi-scale global information. Then, we present a Boundary-Guided Feature Refinement (BGFR) module in the decoding phase, which explicitly leverages the boundary information to refine multi-stage decoding features for better performance. Extensive experiments were conducted on two lung tumor segmentation datasets, including a private dataset (HUST-Lung) and a public benchmark dataset (MSD-Lung). Results show that BGHNet outperforms other state-of-the-art 2D or 3D methods in our experiments, and it exhibits superior generalization performance in both non-contrast and contrast-enhanced CT scans.

Prognostic mutations identified by whole-exome sequencing and validation of the Molecular International Prognostic Scoring System in myelodysplastic syndromes after allogeneic haematopoietic stem cell transplantation.

In this study, we used the whole-exome sequencing (WES) approach to obtain genomic profiles from 92 marrow samples of myelodysplastic syndrome (MDS) patients before haematopoietic stem cell transplantation. We identified 129 mutations in 45 driver genes. Fifty-five patients (59.8%) carried at least 1 driver mutation. The splicing factor U2AF1 was the most frequently mutated in the cohort (21 cases, 23%), followed by BCOR (9 cases, 10%), ASXL1 (8 cases, 9%), TET2 (6 cases, 7%), NPM1 (5 cases, 5%), RUNX1 (5 cases, 5%), and SETBP1 (5 cases, 5%). WES also identified 49 possible oncogenic variants in six genes (PIEZO1, LOXHD1, MYH13, DNAH5, DPH1, and USH2A) that were associated with overall survival (OS) or relapse-free survival (RFS) in MDS after transplantation. Multivariate analysis showed mutations in DNAH5 and USH2A to be independent risk factors for OS. Mutations in DNAH5 and LOXHD1 were risk factors for worse RFS. The Molecular International Prognostic Scoring System retained its independent prognostic significance for RFS after multivariate analysis.

Performance Limits and Advancements in Single 2D Transition Metal Dichalcogenide Transistor.

Two-dimensional (2D) transition metal dichalcogenides (TMDs) allow for atomic-scale manipulation, challenging the conventional limitations of semiconductor materials. This capability may overcome the short-channel effect, sparking significant advancements in electronic devices that utilize 2D TMDs. Exploring the dimension and performance limits of transistors based on 2D TMDs has gained substantial importance. This review provides a comprehensive investigation into these limits of the single 2D-TMD transistor. It delves into the impacts of miniaturization, including the reduction of channel length, gate length, source/drain contact length, and dielectric thickness on transistor operation and performance. In addition, this review provides a detailed analysis of performance parameters such as source/drain contact resistance, subthreshold swing, hysteresis loop, carrier mobility, on/off ratio, and the development of p-type and single logic transistors. This review details the two logical expressions of the single 2D-TMD logic transistor, including current and voltage. It also emphasizes the role of 2D TMD-based transistors as memory devices, focusing on enhancing memory operation speed, endurance, data retention, and extinction ratio, as well as reducing energy consumption in memory devices functioning as artificial synapses. This review demonstrates the two calculating methods for dynamic energy consumption of 2D synaptic devices. This review not only summarizes the current state of the art in this field but also highlights potential future research directions and applications. It underscores the anticipated challenges, opportunities, and potential solutions in navigating the dimension and performance boundaries of 2D transistors.

Inhibitory effects of resveratrol on platelet activation and thrombosis in colon cancer through regulation of the MAPK and cGMP/VASP pathways.

Thrombosis is the primary cause of death in patients with cancer. Resveratrol inhibits platelet activation, a crucial pathophysiological basis of thrombosis, in healthy individuals. However, its effects and mechanisms of action in patients with colon cancer remain unknown. Here, we investigated the effect of resveratrol on platelet adhesion and aggregation in patients with colon cancer. Through numerous in vitro and in vivo analyses, including flow cytometry, western blotting, ELISA, and immunofluorescence and colon cancer rat models, we demonstrated that resveratrol reduced thrombosis in patients with colon cancer by inhibiting the phosphorylation of the MAPK and activating the cyclic-GMP/vasodilator-stimulated phosphoprotein pathway. These findings demonstrate the potential of resveratrol in reducing thrombosis in patients with colon cancer and could be used to develop novel therapeutic strategies for this condition.