Classification of recurrent major depressive disorder using a new time series feature extraction method through multisite rs-fMRI data.

BACKGROUND: Major depressive disorder (MDD) has a high rate of recurrence. Identifying patients with recurrent MDD is advantageous in adopting prevention strategies to reduce the disabling effects of depression. METHOD: We propose a novel feature extraction method that includes dynamic temporal information, and inputs the extracted features into a graph convolutional network (GCN) to achieve classification of recurrent MDD. We extract the average time series using an atlas from resting-state functional magnetic resonance imaging (fMRI) data. Pearson correlation was calculated between brain region sequences at each time point, representing the functional connectivity at each time point. The connectivity is used as the adjacency matrix and the brain region sequences as node features for a GCN model to classify recurrent MDD. Gradient-weighted Class Activation Mapping (Grad-CAM) was used to analyze the contribution of different brain regions to the model. Brain regions making greater contribution to classification were considered to be the regions with altered brain function in recurrent MDD. RESULT: We achieved a classification accuracy of 75.8 % for recurrent MDD on the multi-site dataset, the Rest-meta-MDD. The brain regions closely related to recurrent MDD have been identified. LIMITATION: The pre-processing stage may affect the final classification performance and harmonizing site differences may improve the classification performance. CONCLUSION: The experimental results demonstrate that the proposed method can effectively classify recurrent MDD and extract dynamic changes of brain activity patterns in recurrent depression.

Anticancer Activity of Diosgenin and Its Molecular Mechanism.

Diosgenin, a steroidal sapogenin, obtained from Trigonella foenum-graecum, Dioscorea, and Rhizoma polgonati, has shown high potential and interest in the treatment of various cancers such as oral squamous cell carcinoma, laryngeal cancer, esophageal cancer, liver cancer, gastric cancer, lung cancer, cervical cancer, prostate cancer, glioma, and leukemia. This article aims to provide an overview of the in vivo, in vitro, and clinical studies reporting the diosgenin's anticancer effects. Preclinical studies have shown promising effects of diosgenin on inhibiting tumor cell proliferation and growth, promoting apoptosis, inducing differentiation and autophagy, inhibiting tumor cell metastasis and invasion, blocking cell cycle, regulating immunity and improving gut microbiome. Clinical investigations have revealed clinical dosage and safety property of diosgenin. Furthermore, in order to improve the biological activity and bioavailability of diosgenin, this review focuses on the development of diosgenin nano drug carriers, combined drugs and the diosgenin derivatives. However, further designed trials are needed to unravel the diosgenin's deficiencies in clinical application.

Altered Effective Connectivity Among the Cerebellum and Cerebrum in Patients with Major Depressive Disorder Using Multisite Resting-State fMRI.

Major depressive disorder (MDD) is a serious and widespread psychiatric disorder. Previous studies mainly focused on cerebrum functional connectivity, and the sample size was relatively small. However, functional connectivity is undirected. And, there is increasing evidence that the cerebellum is also involved in emotion and cognitive processing and makes outstanding contributions to the symptomology and pathology of depression. Therefore, we used a large sample size of resting-state functional magnetic resonance imaging (rs-fMRI) data to investigate the altered effective connectivity (EC) among the cerebellum and other cerebral cortex in patients with MDD. Here, from the perspective of data-driven analysis, we used two different atlases to divide the whole brain into different regions and analyzed the alterations of EC and EC networks in the MDD group compared with healthy controls group (HCs). The results showed that compared with HCs, there were significantly altered EC in the cerebellum-neocortex and cerebellum-basal ganglia circuits in MDD patients, which implied that the cerebellum may be a potential biomarker of depressive disorders. And, the alterations of EC brain networks in MDD patients may provide new insights into the pathophysiological mechanisms of depression.

Anticancer Activity of Diosgenin and Its Molecular Mechanism / 中国结合医学杂志

Diosgenin, a steroidal sapogenin, obtained from Trigonella foenum-graecum, Dioscorea, and Rhizoma polgonati, has shown high potential and interest in the treatment of various cancers such as oral squamous cell carcinoma, laryngeal cancer, esophageal cancer, liver cancer, gastric cancer, lung cancer, cervical cancer, prostate cancer, glioma, and leukemia. This article aims to provide an overview of the in vivo, in vitro, and clinical studies reporting the diosgenin's anticancer effects. Preclinical studies have shown promising effects of diosgenin on inhibiting tumor cell proliferation and growth, promoting apoptosis, inducing differentiation and autophagy, inhibiting tumor cell metastasis and invasion, blocking cell cycle, regulating immunity and improving gut microbiome. Clinical investigations have revealed clinical dosage and safety property of diosgenin. Furthermore, in order to improve the biological activity and bioavailability of diosgenin, this review focuses on the development of diosgenin nano drug carriers, combined drugs and the diosgenin derivatives. However, further designed trials are needed to unravel the diosgenin's deficiencies in clinical application.

Anticancer Activity of Diosgenin and Its Molecular Mechanism / 中国结合医学杂志

Diosgenin, a steroidal sapogenin, obtained from Trigonella foenum-graecum, Dioscorea, and Rhizoma polgonati, has shown high potential and interest in the treatment of various cancers such as oral squamous cell carcinoma, laryngeal cancer, esophageal cancer, liver cancer, gastric cancer, lung cancer, cervical cancer, prostate cancer, glioma, and leukemia. This article aims to provide an overview of the in vivo, in vitro, and clinical studies reporting the diosgenin's anticancer effects. Preclinical studies have shown promising effects of diosgenin on inhibiting tumor cell proliferation and growth, promoting apoptosis, inducing differentiation and autophagy, inhibiting tumor cell metastasis and invasion, blocking cell cycle, regulating immunity and improving gut microbiome. Clinical investigations have revealed clinical dosage and safety property of diosgenin. Furthermore, in order to improve the biological activity and bioavailability of diosgenin, this review focuses on the development of diosgenin nano drug carriers, combined drugs and the diosgenin derivatives. However, further designed trials are needed to unravel the diosgenin's deficiencies in clinical application.

The alterations of brain functional connectivity networks in major depressive disorder detected by machine learning through multisite rs-fMRI data.

BACKGROUND: The current diagnosis of major depressive disorder (MDD) is mainly based on the patient's self-report and clinical symptoms. Machine learning methods are used to identify MDD using resting-state functional magnetic resonance imaging (rs-fMRI) data. However, due to large site differences in multisite rs-fMRI data and the difficulty of sample collection, most of the current machine learning studies use small sample sizes of rs-fMRI datasets to detect the alterations of functional connectivity (FC) or network attribute (NA), which may affect the reliability of the experimental results. METHODS: Multisite rs-fMRI data were used to increase the size of the sample, and then we extracted the functional connectivity (FC) and network attribute (NA) features from 1611 rs-fMRI data (832 patients with MDD (MDDs) and 779 healthy controls (HCs)). ComBat algorithm was used to harmonize the data variances caused by the multisite effect, and multivariate linear regression was used to remove age and sex covariates. Two-sample t-test and wrapper-based feature selection methods (support vector machine recursive feature elimination with cross-validation (SVM-RFECV) and LightGBM's "feature_importances_" function) were used to select important features. The Shapley additive explanations (SHAP) method was used to assign the contribution of features to the best classification effect model. RESULTS: The best result was obtained from the LinearSVM model trained with the 136 important features selected by SVMRFE-CV. In the nested five-fold cross-validation (consisting of an outer and an inner loop of five-fold cross-validation) of 1611 data, the model achieved the accuracy, sensitivity, and specificity of 68.90 %, 71.75 %, and 65.84 %, respectively. The 136 important features were tested in a small dataset and obtained excellent classification results after balancing the ratio between patients with depression and HCs. CONCLUSIONS: The combined use of FC and NA features is effective for classifying MDDs and HCs. The important FC and NA features extracted from the large sample dataset have some generalization performance and may be used as a reference for the altered brain functional connectivity networks in MDD.

A strategy of model space search for dynamic causal modeling in task fMRI data exploratory analysis.

Dynamic causal modeling (DCM) is a tool used for effective connectivity (EC) estimation in neuroimage analysis. But it is a model-driven analysis method, and the structure of the EC network needs to be determined in advance based on a large amount of prior knowledge. This characteristic makes it difficult to apply DCM to the exploratory brain network analysis. The exploratory analysis of DCM can be realized from two perspectives: one is to reduce the computational cost of the model; the other is to reduce the model space. From the perspective of model space reduction, a model space exploration strategy is proposed, including two algorithms. One algorithm, named GreedyEC, starts with reducing EC from full model, and the other, named GreedyROI, start with adding EC from one node model. Then the two algorithms were applied to the task state functional magnetic resonance imaging (fMRI) data of visual object recognition and selected the best DCM model from the perspective of model comparison based on Bayesian model compare method. Results show that combining the results of the two algorithms can further improve the effect of DCM exploratory analysis. For convenience in application, the algorithms were encapsulated into MATLAB function based on SPM to help neuroscience researchers to analyze the brain causal information flow network. The strategy provides a model space exploration tool that may obtain the best model from the perspective of model comparison and lower the threshold of DCM analysis.

Diagnostic classification of cancers using DNA methylation of paracancerous tissues.

The potential role of DNA methylation from paracancerous tissues in cancer diagnosis has not been explored until now. In this study, we built classification models using well-known machine learning models based on DNA methylation profiles of paracancerous tissues. We evaluated our methods on nine cancer datasets collected from The Cancer Genome Atlas (TCGA) and utilized fivefold cross-validation to assess the performance of models. Additionally, we performed gene ontology (GO) enrichment analysis on the basis of the significant CpG sites selected by feature importance scores of XGBoost model, aiming to identify biological pathways involved in cancer progression. We also exploited the XGBoost algorithm to classify cancer types using DNA methylation profiles of paracancerous tissues in external validation datasets. Comparative experiments suggested that XGBoost achieved better predictive performance than the other four machine learning methods in predicting cancer stage. GO enrichment analysis revealed key pathways involved, highlighting the importance of paracancerous tissues in cancer progression. Furthermore, XGBoost model can accurately classify nine different cancers from TCGA, and the feature sets selected by XGBoost can also effectively predict seven cancer types on independent GEO datasets. This study provided new insights into cancer diagnosis from an epigenetic perspective and may facilitate the development of personalized diagnosis and treatment strategies.

NecroX-5 ameliorates bleomycin-induced pulmonary fibrosis via inhibiting NLRP3-mediated epithelial-mesenchymal transition.

BACKGROUND: Pulmonary fibrosis is a progressive and usually lethal pulmonary disease. Despite considerable research efforts, no effective therapeutic strategy for pulmonary fibrosis has been developed. NecroX-5 has been reported to possess anti-inflammatory, anti-oxidative and anti-tumor activities. In the present study, we aimed to determine whether NecroX-5 exhibits antifibrotic property in bleomycin (BLM)-induced pulmonary fibrosis. RESULTS: We found that pre-treatment with NecroX-5 alleviated inflammatory response, reduced oxidative stress, inhibited epithelial-mesenchymal transition (EMT), and ameliorated pulmonary fibrosis in vivo and in vitro. Our data further indicated that NecroX-5 substantially reduced activation of NLRP3 inflammasome and TGF-ß1/Smad2/3 signaling in vivo and in vitro. Additionally, NLRP3 overexpression significantly reversed the protective effects of NecroX-5 in lung epithelial cells exposed to BLM. CONCLUSIONS: Overall, our results demonstrate the potent antifibrotic properties of NecroX-5 and its therapeutic potential for pulmonary fibrosis.

Diastereo- and Enantioselective Synthesis of Borylated 3-Hydroxyoxindoles by Addition of gem-Diborylalkanes to Isatins.

The catalytic asymmetric synthesis of borylated 3-hydroxyoxindoles by addition of gem-diborylalkanes to isatins is disclosed. Chiral 3-hydroxyoxindoles bearing two contiguous stereogenic centers were produced in up to >20:1 dr and 99% ee. The synthetic utility of the corresponding products is presented through several transformations of the boryl moiety. This report provides an efficient strategy to incorporate a boryl functional group toward the synthesis of 3-hydroxyoxindoles.

The construction of transcriptional risk scores for breast cancer based on lightGBM and multiple omics data.

BACKGROUND: Polygenic risk score (PRS) can evaluate the individual-level genetic risk of breast cancer. However, standalone single nucleotide polymorphisms (SNP) data used for PRS may not provide satisfactory prediction accuracy. Additionally, current PRS models based on linear regression have insufficient power to leverage non-linear effects from thousands of associated SNPs. Here, we proposed a transcriptional risk score (TRS) based on multiple omics data to estimate the risk of breast cancer. METHODS: The multiple omics data and clinical data of breast invasive carcinoma (BRCA) were collected from the cancer genome atlas (TCGA) and the gene expression omnibus (GEO). First, we developed a novel TRS model for BRCA utilizing single omic data and LightGBM algorithm. Subsequently, we built a combination model of TRS derived from each omic data to further improve the prediction accuracy. Finally, we performed association analysis and prognosis prediction to evaluate the utility of the TRS generated by our method. RESULTS: The proposed TRS model achieved better predictive performance than the linear models and other ML methods in single omic dataset. An independent validation dataset also verified the effectiveness of our model. Moreover, the combination of the TRS can efficiently strengthen prediction accuracy. The analysis of prevalence and the associations of the TRS with phenotypes including case-control and cancer stage indicated that the risk of breast cancer increases with the increases of TRS. The survival analysis also suggested that TRS for the cancer stage is an effective prognostic metric of breast cancer patients. CONCLUSIONS: Our proposed TRS model expanded the current definition of PRS from standalone SNP data to multiple omics data and outperformed the linear models, which may provide a powerful tool for diagnostic and prognostic prediction of breast cancer.

Catalytic Syn-Selective Nitroaldol Approach to Amphenicol Antibiotics: Evolution of a Unified Asymmetric Synthesis of (-)-Chloramphenicol, (-)-Azidamphenicol, (+)-Thiamphenicol, and (+)-Florfenicol.

A unified strategy for an efficient and high diastereo- and enantioselective synthesis of (-)-chloramphenicol, (-)-azidamphenicol, (+)-thiamphenicol, and (+)-florfenicol based on a key catalytic syn-selective Henry reaction is reported. The stereochemistry of the ligand-enabled copper(II)-catalyzed aryl aldehyde Henry reaction of nitroethanol was first explored to forge a challenging syn-2-amino-1,3-diol structure unit with vicinal stereocenters with excellent stereocontrol. Multistep continuous flow manipulations were carried out to achieve the efficient asymmetric synthesis of this family of amphenicol antibiotics.

Altered Effective Connectivity of Children and Young Adults With Unilateral Amblyopia: A Resting-State Functional Magnetic Resonance Imaging Study.

The altered functional connectivity (FC) in amblyopia has been investigated by many studies, but the specific causality of brain connectivity needs to be explored further to understand the brain activity of amblyopia. We investigated whether the effective connectivity (EC) of children and young adults with amblyopia was altered. The subjects included 16 children and young adults with left eye amblyopia and 17 healthy controls (HCs). The abnormalities between the left/right primary visual cortex (PVC) and the other brain regions were investigated in a voxel-wise manner using the Granger causality analysis (GCA). According to the EC results in the HCs and the distribution of visual pathways, 12 regions of interest (ROIs) were selected to construct an EC network. The alteration of the EC network of the children and young adults with amblyopia was analyzed. In the voxel-wise manner analysis, amblyopia showed significantly decreased EC between the left/right of the PVC and the left middle frontal gyrus/left inferior frontal gyrus compared with the HCs. In the EC network analysis, compared with the HCs, amblyopia showed significantly decreased EC from the left calcarine fissure, posterior cingulate gyrus, left lingual gyrus, right lingual gyrus, and right fusiform gyrus to the right calcarine fissure. Amblyopia also showed significantly decreased EC from the right inferior frontal gyrus and right lingual gyrus to the left superior temporal gyrus compared with the HCs in the EC network analysis. The results may indicate that amblyopia altered the visual feedforward and feedback pathway, and amblyopia may have a greater relevance with the feedback pathway than the feedforward pathway. Amblyopia may also correlate with the feedforward of the third visual pathway.

Effect of Dexmedetomidine Combined Electrical Stimulation on Coanitive Function of Patients Receiving Extracerebral Intervention / 中国中西医结合杂志

<p><b>OBJECTIVE</b>To explore the effect of dexmedetomidine combined electrical stimulation on cognitive function of neurosurgical diseases patients treated by extracerebral intervention.</p><p><b>METHODS</b>Totally 122 patients with neurosurgical diseases who underwent selective intervention were randomly assigned to the observation group and the control group, 61 cases in each group. Patients in the control group recieved anesthesia by dexmedetomidine. Those in the observation group received electrical stimulation at Baihui (DU20), Yintang ( EX-HN3), and Neiguan (PC6) before dexmedetomidine anesthesia. The cognitive function of patients at preoperative day 1 and postoperative day 1 was respectively evaluated by Mini-Mental State Examinations (MMSE). Serum NSE, S-100β, IL-1β, IL-6, and TNF-α levels were detected in the two groups before intervention and immediately after intervention using ELISA.</p><p><b>RESULTS</b>MMSE scores of two groups were significantly reduced at post-intervention day 1, as compared with one day before intervention. MMSE score of the observation group at post-intervention day 1 was (23.15 ± 1.87) points, significantly higher than that of the control group [ (19.34 ± 1.64) points , (P < 0.05)]. The postoperative cognitive dysfunction (POCD) incidence rate of the observation group was 16.4% (10/61), significantly lower than that of the control group [39.3% (24/61); P < 0.05]. Compared with before intervention, NSE and S-100β protein levels, IL-1β, IL-6 and α-TNF levels of the two groups increased (P < 0.05). Post-intervention NSE and S-100β protein levels, IL-1β, IL-6 and α-TNF levels were significantly lower in the observation group than in the control group (P < 0.05).</p><p><b>CONCLUSION</b>Dexmedetomidine combied electrical stimulation could effectively prevent the occurrence of postoperative cognition, and reduce levels of NSA, S-100β, IL-1β, IL-6 and TNF-α.</p>

[Characterization of novel alleles and new mutation sites of porcine MHC class II DQA].

The primers, DQAp161 and DQAp443, were designed based on the homologous region of SLA-DQA cDNA sequences and HLA-DQA genomic sequences. The 731 bp fragment of SLA-DQA including completed intron 2, the near completed exon 2 and partial exon 3 was obtained by PCR. The nucleotide sequences of the fragment of SLA-DQA were obtained with cloning and direct sequencing. Both nucleotide sequences of exon 2 and amino acid sequences of alpha 1 domain were analyzed in a pedigree. The sequence data were compared with all sequences of SLA-DQA exon 2 in GenBank. Two novel alleles, DQA-SLT 26 and DQA-TC 21-1, were found according to the above analyses. Four amino acid changes were observed among SLA-DQA haplotype c, d and DQA-SLT 26. They were Val-->Ala(60), Lys-->Glu(65), Asp-->Gly(81) and Lys-->Ile(93). Comparing the amino acids sequence of the all SLA-DQA sequences with DQA-TC 21-1 revealed that the His (94) was changed into Tyr.

Genetic variation and relationships of eighteen Chinese indigenous pig breeds.

Chinese indigenous pig breeds are recognized as an invaluable component of the world's pig genetic resources and are divided traditionally into six types. Twenty-six microsatellite markers recommended by the FAO (Food and Agriculture Organization) and ISAG (International Society of Animal Genetics) were employed to analyze the genetic diversity of 18 Chinese indigenous pig breeds with 1001 individuals representing five types, and three commercial breeds with 184 individuals. The observed heterozygosity, unbiased expected heterozygosity and the observed and effective number of alleles were used to estimate the genetic variation of each indigenous breed. The unbiased expected heterozygosity ranged between 0.700 (Mashen) and 0.876 (Guanling), which implies that there is an abundant genetic variation stored in Chinese indigenous pig breeds. Breed differentiation was shown by fixation indices (FIT, FIS, and FST). The FST per locus varied from 0.019 (S0090) to 0.170 (SW951), and the average FST of all loci was 0.077, which means that most of the genetic variation was kept within breeds and only a little of the genetic variation exists between populations. The Neighbor-Joining tree was constructed based on the Nei DA (1978) distances and one large cluster with all local breeds but the Mashen breed, was obtained. Four smaller sub-clusters were also found, which included two to four breeds each. These results, however, did not completely agree with the traditional type of classification. A Neighbor-Joining dendrogram of individuals was established from the distance of -ln(proportions of shared alleles); 92.14% of the individuals were clustered with their own breeds, which implies that this method is useful for breed demarcation. This extensive research on pig genetic diversity in China indicates that these 18 Chinese indigenous breeds may have one common ancestor, helps us to better understand the relative distinctiveness of pig genetic resources, and will assist in developing a national plan for the conservation and utilization of Chinese indigenous pig breeds.

Single-dose ceftriaxone versus multiple-dose cefuroxime for prophylaxis of surgical site infection / 中华外科杂志

<p><b>OBJECTIVE</b>To compare the effects and pharmacoeconomics of single-dose of ceftriaxone versus 3-day cefuroxime prophylaxis in patients undergoing gastric or colorectal resection.</p><p><b>METHODS</b>Three hundred and five consecutive patients with gastric or colorectal cancer from 5 medical centers were randomly divided into ceftriaxone group (n = 153, receiving intravenously 1 g ceftriaxone 0.5 - 1 h prior to operation only) and cefuroxime group (n = 152, receiving 0.75 g cefuroxime preoperatively and the same dose q8h for 3 d). The patients' intra- and postoperative status, adverse responses and infectious complications were observed and documented, and pharmacoeconomic parameters were analyzed.</p><p><b>RESULTS</b>The disease distribution, operative procedures and patients' conditions in the 2 groups were comparable. No adverse responses to the test antibiotics were observed. Postoperative infectious complications occurred in 7 cases in the ceftriaxone group (4.58%) and 14 cases in the cefuroxime group (9.21%), respectively (P = 0.992), among which, 12 cases were surgical site infections (incisional, intra-abdominal): 2 cases in the ceftriaxone group (1.31%), and 10 cases in the cefuroxime group (6.58%), (chi(2) = 5.607, P = 0.018). The direct cost related to prevention and treatment of surgical site infections was 283.5 RMB in the ceftriaxone group and 811.1 RMB in the cefuroxime group (Z = 14.51, P = 0.000).</p><p><b>CONCLUSION</b>Both ceftriaxone and cefuroxime are safe and effective for prevention of surgical site infections. Single-dose ceftriaxone prophylaxis is sufficient for gastric and colorectal operations, with a better cost-effectiveness ratio.</p>

Genetic relationships among twelve Chinese indigenous goat populations based on microsatellite analysis.

Twelve Chinese indigenous goat populations were genotyped for twenty-six microsatellite markers recommended by the EU Sheep and Goat Biodiversity Project. A total of 452 goats were tested. Seventeen of the 26 microsatellite markers used in this analysis had four or more alleles. The mean expected heterozygosity and the mean observed heterozygosity for the population varied from 0.611 to 0.784 and 0.602 to 0.783 respectively. The mean FST (0.105) demonstrated that about 89.5% of the total genetic variation was due to the genetic differentiation within each population. A phylogenetic tree based on the Nei (1978) standard genetic distance displayed a remarkable degree of consistency with their different geographical origins and their presumed migration throughout China. The correspondence analysis did not only distinguish population groups, but also confirmed the above results, classifying the important populations contributing to diversity. Additionally, some specific alleles were shown to be important in the construction of the population structure. The study analyzed the recent origins of these populations and contributed to the knowledge and genetic characterization of Chinese indigenous goat populations. In addition, the seventeen microsatellites recommended by the EU Sheep and Goat Biodiversity Project proved to be useful for the biodiversity studies in goat breeds.

[Isolation, localization and expression of a novel expressed sequence tag from pig skeletal muscular tissue].

A novel expressed sequence tag (ESThp9-1, GenBank accession number: B1596262) was isolated from pig skeletal muscular tissue by using the mRNA differential display technique. BLAST analysis revealed that the 196 bp long EST (ESThp9-1) was not homologous to any of the known porcine genes in the database but similar to rat U3A small nuclear RNA (87% identity over 93 nucleotides) and mouse U3B.4 small nuclear RNA (85% identity over 96 nucleotides). Semi-quantitative reverse transcription polymerase chain reaction indicated that EST9hp-1 was expressed in most of tissue of the pig. ESThp9-1 was physically mapped on sus scrofa chromosome 12q1.1-q1.5 and linked with microsatellite S0090 by using somatic cell hybrid panel and radiation hybrid panel analysis. According to the homologous information and result of physical mapping, ESThp9-1 was presumed to be one member of the porcine U3 gene family.

Preparation and analysis of spermatocyte meiotic pachytene bivalents of pigs for gene mapping.

Well-spread meiotic pachytene bivalents were obtained by using the prolonged hypotonic treatment combined with high chloroform Carnory's fixative solution from cells of the testes of domestic pigs. Comparison in the division index and length of pachytene bivalents with metaphase chromosomes showed that those of the former are 5 times higher and 3.42(1.87-5.98) times longer than those of the latter. Comparative studies on chromomere maps of bivalents and mitotic chromosomal G-bands were conducted by using the chromosome 12 as a example. Sex vesicle and various shapes of synaptic sex chromosomes have been observed. Two-color PRimed IN Situ (PRINS) labeling has been conducted successfully on pachytene bivalents of pigs.