Distillation of multi-class cervical lesion cell detection via synthesis-aided pre-training and patch-level feature alignment.

Automated detection of cervical abnormal cells from Thin-prep cytologic test (TCT) images is crucial for efficient cervical abnormal screening using computer-aided diagnosis systems. However, the construction of the detection model is hindered by the preparation of the training images, which usually suffers from issues of class imbalance and incomplete annotations. Additionally, existing methods often overlook the visual feature correlations among cells, which are crucial in cervical lesion cell detection as pathologists commonly rely on surrounding cells for identification. In this paper, we propose a distillation framework that utilizes a patch-level pre-training network to guide the training of an image-level detection network, which can be applied to various detectors without changing their architectures during inference. The main contribution is three-fold: (1) We propose the Balanced Pre-training Model (BPM) as the patch-level cervical cell classification model, which employs an image synthesis model to construct a class-balanced patch dataset for pre-training. (2) We design the Score Correction Loss (SCL) to enable the detection network to distill knowledge from the BPM model, thereby mitigating the impact of incomplete annotations. (3) We design the Patch Correlation Consistency (PCC) strategy to exploit the correlation information of extracted cells, consistent with the behavior of cytopathologists. Experiments on public and private datasets demonstrate the superior performance of the proposed distillation method, as well as its adaptability to various detection architectures.

Nucleus-Aware Self-Supervised Pretraining Using Unpaired Image-to-Image Translation for Histopathology Images.

Self-supervised pretraining attempts to enhance model performance by obtaining effective features from unlabeled data, and has demonstrated its effectiveness in the field of histopathology images. Despite its success, few works concentrate on the extraction of nucleus-level information, which is essential for pathologic analysis. In this work, we propose a novel nucleus-aware self-supervised pretraining framework for histopathology images. The framework aims to capture the nuclear morphology and distribution information through unpaired image-to-image translation between histopathology images and pseudo mask images. The generation process is modulated by both conditional and stochastic style representations, ensuring the reality and diversity of the generated histopathology images for pretraining. Further, an instance segmentation guided strategy is employed to capture instance-level information. The experiments on 7 datasets show that the proposed pretraining method outperforms supervised ones on Kather classification, multiple instance learning, and 5 dense-prediction tasks with the transfer learning protocol, and yields superior results than other self-supervised approaches on 8 semi-supervised tasks. Our project is publicly available at https://github.com/zhiyuns/UNITPathSSL.

The Entry and Egress of Monocytes in Atherosclerosis: A Biochemical and Biomechanical Driven Process.

In accordance with "the response to injury" theory, the entry of monocytes into the intima guided by inflammation signals, taking up cholesterol and transforming into foam cells, and egress from plaques determines the progression of atherosclerosis. Multiple cytokines and receptors have been reported to be involved in monocyte recruitment such as CCL2/CCR2, CCL5/CCR5, and CX3CL1/CX3CR1, and the egress of macrophages from the plaque like CCR7/CCL19/CCL21. Interestingly, some neural guidance molecules such as Netrin-1 and Semaphorin 3E have been demonstrated to show an inhibitory effect on monocyte migration. During the processes of monocytes recruitment and migration, factors affecting the biomechanical properties (e.g., the membrane fluidity, the deformability, and stiffness) of the monocytes, like cholesterol, amyloid-ß peptide (Aß), and lipopolysaccharides (LPS), as well as the biomechanical environment that the monocytes are exposed, like the extracellular matrix stiffness, mechanical stretch, blood flow, and hypertension, were discussed in the latter section. Till now, several small interfering RNAs (siRNAs), monoclonal antibodies, and antagonists for CCR2 have been designed and shown promising efficiency on atherosclerosis therapy. Seeking more possible biochemical factors that are chemotactic or can affect the biomechanical properties of monocytes, and uncovering the underlying mechanism, will be helpful in future studies.

The Basic Properties of Gold Nanoparticles and their Applications in Tumor Diagnosis and Treatment.

Gold nanoparticles (AuNPs) have been widely studied and applied in the field of tumor diagnosis and treatment because of their special fundamental properties. In order to make AuNPs more suitable for tumor diagnosis and treatment, their natural properties and the interrelationships between these properties should be systematically and profoundly understood. The natural properties of AuNPs were discussed from two aspects: physical and chemical. Among the physical properties of AuNPs, localized surface plasmon resonance (LSPR), radioactivity and high X-ray absorption coefficient are widely used in the diagnosis and treatment of tumors. As an advantage over many other nanoparticles in chemicals, AuNPs can form stable chemical bonds with S-and N-containing groups. This allows AuNPs to attach to a wide variety of organic ligands or polymers with a specific function. These surface modifications endow AuNPs with outstanding biocompatibility, targeting and drug delivery capabilities. In this review, we systematically summarized the physicochemical properties of AuNPs and their intrinsic relationships. Then the latest research advancements and the developments of basic research and clinical trials using these properties are summarized. Further, the difficulties to be overcome and possible solutions in the process from basic laboratory research to clinical application are discussed. Finally, the possibility of applying the results to clinical trials was estimated. We hope to provide a reference for peer researchers to better utilize the excellent physicochemical properties of gold nanoparticles in oncotherapy.

Sp7/osterix positively regulates dlx2b and bglap to affect tooth development and bone mineralization in zebrafish larvae.

Osterix (or Sp7) is an important transcription factor that promotes osteoblast differentiation by modulating the expression of a range of target genes. Although many studies have focused on Osterix/Sp7 regulatory mechanisms, the detailed functions have not been fully elucidated. Toward this end, in this study, we used CRISPR/Cas9 technology to knock out the zebrafish sp7 gene, and then analyzed its phenotype and biological function. Two knockout sp7 mutant lines were successfully obtained. The bone mineralization level was significantly reduced in the zebrafish sp7-/- homozygote, resulting in abnormal tooth development in the larvae. Quantitative real-time polymerase chain reaction showed that loss of sp7 led to down-regulated expression of the dlx2b and bglap genes related to tooth development and bone mineralization, respectively. Moreover, cell transfection experiments demonstrated that Sp7 directly regulates the expression of dlx2b and bglap through Sp7-binding sites on the promoter regions of these two genes. Overall, this study provides new insight into the role of Sp7 in bone mineralization and tooth development.

The expression of resistin in adipose tissues of patients with polycystic ovary syndrome and insulin resistance.

The relationship between the expression of resistin in polycystic ovary syndrome (PCOS) and insulin resistance was investigated. The plasma resistin concentrations in 35 patients with PCOS and 40 controls were measured by ELISA. Luteinizing hormone (LH), follicle-stimulating hormone (FSH), and fasting insulin (FIN) were tested by radioimmunoassay. Insulin resistance index (HOMA-IR) was calculated. Fasting plasma glucose (FPG) was determined by oxidase test. Western blot and reverse transcriptase PCR (RT-PCR) methods were used to detect the expression of resistin in adipose tissues. The levels of plasma resistin, LH, LH/FSH and FIN and HOMA-IR in patients with PCOS were significantly higher than those in control group (all P<0.05). Plasma resistin was correlated positively with FPG, FIN, HOMA-IR, LH and LH/FSH (r=0.56, 0.60, 0.65, 0.48, and 0.42 respectively). Resistin protein and mRNA expression levels in patients with PCOS were significantly higher than those in normal tissues (all P<0.01). It was concluded that resistin might be involved in the pathogenesis of insulin resistance of PCOS.

The Expression of Resistin in Adipose Tissues of Patients with Polycystic Ovary Syndrome and Insulin Resistance / 华中科技大学学报（医学）（英德文版）

The relationship between the expression of resistin in polycystic ovary syndrome (PCOS) and insulin resistance was investigated. The plasma resistin concentrations in 35 patients with PCOS and 40 controls were measured by ELISA. Luteinizing hormone (LH), follicle-stimulating hormone (FSH), and fasting insulin (FIN) were tested by radioimmunoassay. Insulin resistance index (HOMA-IR) was calculated. Fasting plasma glucose (FPG) was determined by oxidase test. Western blot and reverse transcriptase PCR (RT-PCR) methods were used to detect the expression of resistin in adipose tissues.The levels of plasma resistin, LH, LH/FSH and FIN and HOMA-IR in patients with PCOS were sig-nificantly higher than those in control group (all P<0.05). Plasma resistin was correlated positively with FPG, FIN, HOMA-IR, LH and LH/FSH (r=0.56, 0.60, 0.65, 0.48, and 0.42 respectively). Resistin pro-tein and mRNA expression levels in patients with PCOS were significantly higher than those in normal tissues (all P<0.01). It was concluded that resistin might be involved in the pathogenesis of insulin re-sistance of PCOS.