Cross-species scRNA-seq reveals the cellular landscape of retina and early alterations in type 2 diabetes mice.

Single-cell RNA sequencing (scRNA-seq) analysis have provided an unprecedented resolution for the studies on diabetic retinopathy (DR). However, the early changes in the retina in diabetes remain unclear. A total of 8 human and mouse scRNA-seq datasets, containing 276,402 cells were analyzed individually to comprehensively delineate the retinal cell atlas. The neural retinas were isolated from the type 2 diabetes (T2D) and control mice, and scRNA-seq analysis was conducted to evaluate the early effects of diabetes on the retina. Bipolar cell (BC) heterogeneity were identified. We found some stable BCs across multiple datasets, and explored their biological functions. A new RBC subtype (Car8_RBC) in the mouse retina was validated using the multi-color immunohistochemistry. AC149090.1 was significantly upregulated in the rod cells, ON cone BCs (CBCs), OFF CBCs, and RBCs in T2D mice. Additionally, the interneurons, especially BCs, were the most vulnerable cells to diabetes by integrating scRNA-seq and genome-wide association studies (GWAS) analyses. In conclusion, this study delineated a cross-species retinal cell atlas and uncovered the early pathological alterations in the retina of T2D mice.

[Clinical characteristics and treatment in adults and children with histiocytic necroti-zing lymphadenitis].

OBJECTIVE: To analyze the clinical data of histiocytic necrotizing lymphadenitis(HNL), comparing the similarities and differences between children and adults, to deepen the understanding of the disease by clinical physicians, and to improve diagnostic rate and reduce misdiagnosis and mistreatment. METHODS: The clinical data of hospitalized patients with histiocytic necrotizing lymphadenitis diagnosed by biopsy from January 2010 to August 2023 in Peking University First Hospital were collec-ted, and the clinical features, laboratory examinations, pathological features, treatments with antibiotics and glucocorticoids, and prognosis of histiocytic necrotic lymphadenitis were analyzed. Grouped based on age, the differences of clinical characteristics, laboratory tests, treatment, and prognosis between the children group (< 16 years old) and the adult group (≥16 years old) were compared. RESULTS: Among the 81 enrolled patients, there were 42 males and 39 females. The median age was 21(14, 29) years, the median duration of disease was 20.0(13.0, 30.0) days, and the median length of hospital stay was 13.0 (10.0, 15.0) days. The first symptoms were fever, lymphadenopathy, and both. All the patients had enlarged lymph nodes with different parts and sizes, 96.3% (78 of 81) of the patients had cervical lymphadenopathy, 50.6% (41 of 81) had bilateral cervical lymphadenopathy, 55.6% (45 of 81) had supraclavicular, axillary or inguinal lymphadenopathy, and the median lymph node diameter was 20.0(20.0, 30.0) mm. Only one patient had no fever, the other 80 patients had fever, the median peak body temperature was 39.0(38.0, 39.8) ℃. Accompanying symptoms: rash (8.6%, 7/81), fatigue (34.6%, 28/81), night sweating (8.6%, 7/81), chills (25.3%, 25/81), muscle soreness (13.6%, 11/81), and joint pain (6.2%, 5/81). There were 17 cases (21.0%, 17/81) of hepatosplenomegaly, of which 12 cases (70.6%, 12/17) were splenomegaly. 68.8%(55/80) of patients had a decrease in white blood cell (WBC) count, with 47.5%(38/80)increased in lymphocyte(LY)proportion, 53.4%(39/73) increased in high-sensitivity C-reactive protein(CRP), 79.2%(57/72) increased in erythrocyte sedimentation rate(ESR), 22.2%(18/81) increased in alanine transaminase(ALT), 27.2%(22/81) elevated in aspartate transaminase(AST), and 81.6%(62/76) elevated in lactate dehydrogenase(LDH). All the 81 patients underwent lymph node biopsy, and 77.8%(63/81) of the patients showed that most of the structures in the lymph nodes were destroyed or disappeared, and 16.0%(13/81) of the lymph nodes were still in existence, hyperplasia and normal lymph node were 1.2%(1/81) respectively, and 3.7%(3/81) had normal lymph node structures. Immunohistochemical staining was performed in 67 cases. The percentages of CD3+ and CD68(KP1)+ were respectively 97.0%(65/67), and MPO+ were 94.0%(63/67). In the study, 51 patients (63.0%, 51/81) were treated with glucocorticoid therapy after diagnosis. The median time for temperature to return to normal was 1.0(1.0, 4.0) days after glucocorticoid therapy. when the glucocorticoid treatment worked best, the body temperature could drop to normal on the same day. There were significant differences in length of stay, predisposing factors, chills, the rate of increase in high-sensitivity CRP, antibiotic and glucocorticoid treatment between the adults and children groups (P < 0.05). CONCLUSION: In clinical practice, if there are cases with unexplained fever, superficial lymph node enlargement, and reduced white blood cells as clinical characteristics, and general antibiotics treatment is ineffective, histiocytic necrotic lymphadenitis should be considered. Lymph node biopsy should be performed as early as possible to clarify the diagnosis, reduce misdiagnosis and mistreatment, and symptomatic treatment should be the main treatment. Glucocorticoids therapy has a definite therapeutic effect.

Immune profiling and prognostic model of pancreatic cancer using quantitative pathology and single-cell RNA sequencing.

BACKGROUND: Pancreatic ductal adenocarcinoma (PDAC) has a complex tumor immune microenvironment (TIME), the clinical value of which remains elusive. This study aimed to delineate the immune landscape of PDAC and determine the clinical value of immune features in TIME. METHODS: Univariable and multivariable Cox regression analyses were performed to evaluate the clinical value of immune features and establish a new prognostic model. We also conducted single-cell RNA sequencing (scRNA-seq) to further characterize the immune profiles of PDAC and explore cell-to-cell interactions. RESULTS: There was a significant difference in the immune profiles between PDAC and adjacent noncancerous tissues. Several novel immune features were captured by quantitative pathological analysis on multiplex immunohistochemistry (mIHC), some of which were significantly correlated with the prognosis of patients with PDAC. A risk score-based prognostic model was established based on these immune features. We also constructed a user-friendly nomogram plot to predict the overall survival (OS) of patients by combining the risk score and clinicopathological features. Both mIHC and scRNA-seq analysis revealed PD-L1 expression was low in PDAC. We found that PD1 + cells were distributed in different T cell subpopulations, and were not enriched in a specific subpopulation. In addition, there were other conserved receptor-ligand pairs (CCL5-SDC1/4) besides the PD1-PD-L1 interaction between PD1 + T cells and PD-L1 + tumor cells. CONCLUSION: Our findings reveal the immune landscape of PDAC and highlight the significant value of the combined application of mIHC and scRNA-seq for uncovering TIME, which might provide new clues for developing immunotherapy combination strategies.

Efficacy of anti-osteoporosis treatment for men with osteoporosis: a meta-analysis.

INTRODUCTION: Osteoporosis and fracture are important healthcare problems for men worldwide, which are relevant to severe disability and mortality. This meta-analysis aimed to assess the effectiveness of pharmacological therapy in men with osteoporosis, and to provide evidence-based hints for clinical practice. MATERIALS AND METHODS: PubMed, Embase, Web of Science were searched from inception to July 31, 2022. Pooled standardized mean difference (SMD) and relative risk (RR) were calculated. Heterogeneity between included studies and publication bias were detected. RESULTS: Twenty clinical studies were enrolled in this meta-analysis. The pooled SMD for mean percentage differences of change from baseline in lumbar spine BMD between the treatment group and the control group was 4.95 (95% CI 2.48, 7.42, I2 = 99%, p < 0.0001). For mean percentage differences of change in femoral neck BMD, the overall SMD was 3.08 (95% CI 0.95, 5.20, I2 = 99%, p = 0.0045). For a change in total hip BMD, the overall SMD was 1.06 (95% CI 0.50, 1.63, I2 = 82%, p = 0.0002). The overall RR for incident vertebral fractures was 0.50 (95% CI 0.37, 0.68, I2 = 5%, p = 0.3971). The pooled RR for nonvertebral fractures and clinical fracture were 0.74 (95% CI 0.41, 1.33, I2 = 28%, p = 0.3139) and 0.81 (95% CI 0.54, 1.21, I2 = 0%, p = 0.2992). CONCLUSION: Findings in this meta-analysis indicate that pharmacological treatment increases lumbar spine, femoral neck, total hip BMD, and decreases incident vertebral fractures in men with osteoporosis.

Momentum contrast transformer for COVID-19 diagnosis with knowledge distillation.

Intelligent diagnosis has been widely studied in diagnosing novel corona virus disease (COVID-19). Existing deep models typically do not make full use of the global features such as large areas of ground glass opacities, and the local features such as local bronchiolectasis from the COVID-19 chest CT images, leading to unsatisfying recognition accuracy. To address this challenge, this paper proposes a novel method to diagnose COVID-19 using momentum contrast and knowledge distillation, termed MCT-KD. Our method takes advantage of Vision Transformer to design a momentum contrastive learning task to effectively extract global features from COVID-19 chest CT images. Moreover, in transfer and fine-tuning process, we integrate the locality of convolution into Vision Transformer via special knowledge distillation. These strategies enable the final Vision Transformer simultaneously focuses on global and local features from COVID-19 chest CT images. In addition, momentum contrastive learning is self-supervised learning, solving the problem that Vision Transformer is challenging to train on small datasets. Extensive experiments confirm the effectiveness of the proposed MCT-KD. In particular, our MCT-KD is able to achieve 87.43% and 96.94% accuracy on two publicly available datasets, respectively.

Effects of calorie intake and sampling time on thyroid stimulating hormone concentration.

BACKGROUND: This study aimed to investigate the effects of blood sampling after calorie intake on thyroid stimulating hormone (TSH) level, compared with blood sampling in fasting state. METHODS: This was a prospective, randomized, controlled study. Subjects from the outpatients in the department of endocrinology without evidence of thyroid diseases were included and then randomized into the fasting group, diet intake group, and glucose intake group, respectively. Fasting blood was collected from all subjects at 7:00 am for the measurement of TSH and free thyroxine (FT4) concentrations. Afterwards, the subjects were maintained at fasting state (fasting group), had an intake of the mixed diet with 400 kcal calories (diet intake group), and had an intake of 75 g glucose (glucose intake group), respectively, and blood was collected again 2 h later (9:00 am on the same day) for TSH and FT4 level measurement and comparison. RESULTS: A total of 150 subjects were enrolled, of whom 146 met the inclusion criteria, with 48, 48, and 50 in the diet intake group, glucose intake group, and fasting group, respectively. The TSH in the diet intake group was significantly lower at 9:00 am (TSH9am) than the level at 7:00 am (TSH7am) (P < 0.001), with a median variation of -0.71 mU/L, and a median variation rate of -32.4%. In the glucose intake group, TSH9am was also significantly lower than TSH7am (P < 0.001), with a median variation of -0.73 mU/L, and a median variation rate of -31.5%. For the fasting group, TSH9am decreased slightly but was significantly lower than TSH7am (P < 0.001), with a median variation of -0.1 mU/L, and a median variation rate of -5.2%. According to TSH7am measurements, 9 subjects (3 subjects in each group) met the diagnostic criteria of subclinical hypothyroidism. However, according toTSH9am measurements, only 2 patients in the fasting group met the diagnostic criteria of subclinical hypothyroidism. CONCLUSION: Compared with the fasting state, the TSH level at 2 h after the calorie intake was decreased by about 30%, which might influence the diagnosis of subclinical hypothyroidism. TRIAL REGISTRATION: ChiCTR2100047454 (18/06/2021).

A novel GNAS mutation in pseudohypoparathyroidism type 1a in a Chinese man presented with recurrent seizure: a case report.

BACKGROUND: Pseudohypoparathyroidism is a rare genetic disease characterized by hypocalcaemia and hyperphosphataemia due to the defect to the guanine nucleotide-binding protein alpha subunit (GNAS) gene. Patients with pseudoparathyroidism type 1a and 1c could manifest Albright's hereditary osteodystrophy and multiple hormone resistance including gonadotropin and thyroid stimulating hormone. CASE PRESENTATION: Here we report a Chinese man who presented with fatigue, recurrent seizure and Albright's hereditary osteodystrophy. His genetic study revealed a heterozygote mutation in the GNAS gene [NM_000516.4(GNAS): c2787_2788del (p.Val930AspfsTer12)]. After calcium and calcitriol supplement, his seizures achieved partially remission. CONCLUSIONS: We report a case of PHP1a or 1c with a novel frameshift mutation in GNAS gene in a patient presenting with AHO, as well as TSH and partial gonadotropin resistance. This mutation in this case has not been reported in literature and adds to the spectrum of genetic mutations related to PHP.

The roles and responsibilities of general practice nurses in China: a qualitative study.

BACKGROUND: General hospitals in China have been establishing General Practice Departments (GPD). Although General Practice Nurses (GPNs) are an important part of this medical system, their training has not been synchronised. This study explored the working status of nurses in GPDs in general hospitals in Beijing to provide a theoretical basis for the training and development of GPNs in China. METHODS: We conducted in-depth, individual interviews with outpatient nurses at 19 hospitals in Beijing between March and April 2021. We employed a qualitative analysis to interpret participant narratives and used a codebook thematic analysis to analyse the interview data and extract themes. RESULTS: The analysis revealed four themes: (i) a lack of full-time GPNs in GPDs of most tertiary hospitals, (ii) the inability of GPNs to fully express their potential and skills owing to their limited roles, (iii) insufficient standardised patient education provided by nurses in GPDs, and (iv) a lack of systematic and relevant training for nurses working in general practice settings. CONCLUSIONS: To promote the development of GPNs, GPDs in general hospitals in China should hire full-time GPNs, define their job duties in alignment with their values, and provide standardised training to strengthen their core competencies.

Consistency Between Thyrotropin Receptor Antibody (TRAb) and Thyroid-Stimulating Antibody (TSAb) Levels in Patients with Graves Disease.

OBJECTIVE: To investigate the consistency between thyrotropin receptor antibody (TRAb) and thyroid-stimulating antibody (TSAb) levels in patients with Graves disease (GD). METHODS: We performed a cross-sectional observational study to recruit eligible patients with GD who visited the outpatient endocrinology clinic for the purpose of evaluating the consistency between their TRAb and TSAb levels. Our cohort included 28 men and 99 women. RESULTS: The median levels of TRAb and TSAb were 5.65 IU/L and 3.76 IU/L, respectively, in the enrolled patients with GD. The levels of TRAb (5.03 vs 8.42 IU/L; P = .008) and TSAb (2.69 vs 5.37 IU/L; P = .008) in patients with adequate thyroid regulation were all lower than those in patients with inadequate thyroid regulation. CONCLUSIONS: Although TRAb is closely related to TSAb, we observed high heterogeneity of TRAb due to relatively low consistency between the levels of the 2 antibodies.

Latent feature representation learning for Alzheimer's disease classification.

Early detection and treatment of Alzheimer's Disease (AD) are significant. Recently, multi-modality imaging data have promoted the development of the automatic diagnosis of AD. This paper proposes a method based on latent feature fusion to make full use of multi-modality image data information. Specifically, we learn a specific projection matrix for each modality by introducing a binary label matrix and local geometry constraints and then project the original features of each modality into a low-dimensional target space. In this space, we fuse latent feature representations of different modalities for AD classification. The experimental results on Alzheimer's Disease Neuroimaging Initiative database demonstrate the proposed methods effectiveness in classifying AD.

Single-cell RNA-seq transcriptomic landscape of human and mouse islets and pathological alterations of diabetes.

Single-cell RNA sequencing has paved the way for delineating the pancreatic islet cell atlas and identifying hallmarks of diabetes. However, pathological alterations of type 2 diabetes (T2D) remain unclear. We isolated pancreatic islets from control and T2D mice for single-cell RNA sequencing (scRNA-seq) and retrieved multiple datasets from the open databases. The complete islet cell landscape and robust marker genes and transcription factors of each endocrine cell type were identified. GLRA1 was restricted to beta cells, and beta cells exhibited obvious heterogeneity. The beta subcluster in the T2D mice remarkably decreased the expression of Slc2a2, G6pc2, Mafa, Nkx6-1, Pdx1, and Ucn3 and had higher unfolded protein response (UPR) scores than in the control mice. Moreover, we developed a Web-based interactive tool, creating new opportunities for the data mining of pancreatic islet scRNA-seq datasets. In conclusion, our work provides a valuable resource for a deeper understanding of the pathological mechanism underlying diabetes.

Transferred Subspace Learning Based on Non-negative Matrix Factorization for EEG Signal Classification.

EEG signal classification has been a research hotspot recently. The combination of EEG signal classification with machine learning technology is very popular. Traditional machine leaning methods for EEG signal classification assume that the EEG signals are drawn from the same distribution. However, the assumption is not always satisfied with the practical applications. In practical applications, the training dataset and the testing dataset are from different but related domains. How to make best use of the training dataset knowledge to improve the testing dataset is critical for these circumstances. In this paper, a novel method combining the non-negative matrix factorization technology and the transfer learning (NMF-TL) is proposed for EEG signal classification. Specifically, the shared subspace is extracted from the testing dataset and training dataset using non-negative matrix factorization firstly and then the shared subspace and the original feature space are combined to obtain the final EEG signal classification results. On the one hand, the non-negative matrix factorization can assure to obtain essential information between the testing and the training dataset; on the other hand, the combination of shared subspace and the original feature space can fully use all the signals including the testing and the training dataset. Extensive experiments on Bonn EEG confirmed the effectiveness of the proposed method.

High-Order Laplacian Regularized Low-Rank Representation for Multimodal Dementia Diagnosis.

Multimodal heterogeneous data, such as structural magnetic resonance imaging (MRI), positron emission tomography (PET), and cerebrospinal fluid (CSF), are effective in improving the performance of automated dementia diagnosis by providing complementary information on degenerated brain disorders, such as Alzheimer's prodromal stage, i.e., mild cognitive impairment. Effectively integrating multimodal data has remained a challenging problem, especially when these heterogeneous data are incomplete due to poor data quality and patient dropout. Besides, multimodal data usually contain noise information caused by different scanners or imaging protocols. The existing methods usually fail to well handle these heterogeneous and noisy multimodal data for automated brain dementia diagnosis. To this end, we propose a high-order Laplacian regularized low-rank representation method for dementia diagnosis using block-wise missing multimodal data. The proposed method was evaluated on 805 subjects (with incomplete MRI, PET, and CSF data) from the real Alzheimer's Disease Neuroimaging Initiative (ADNI) cohort. Experimental results suggest the effectiveness of our method in three tasks of brain disease classification, compared with the state-of-the-art methods.

Research of Low-Rank Representation and Discriminant Correlation Analysis for Alzheimer's Disease Diagnosis.

As population aging is becoming more common worldwide, applying artificial intelligence into the diagnosis of Alzheimer's disease (AD) is critical to improve the diagnostic level in recent years. In early diagnosis of AD, the fusion of complementary information contained in multimodality data (e.g., magnetic resonance imaging (MRI), positron emission tomography (PET), and cerebrospinal fluid (CSF)) has obtained enormous achievement. Detecting Alzheimer's disease using multimodality data has two difficulties: (1) there exists noise information in multimodal data; (2) how to establish an effective mathematical model of the relationship between multimodal data? To this end, we proposed a method named LDF which is based on the combination of low-rank representation and discriminant correlation analysis (DCA) to fuse multimodal datasets. Specifically, the low-rank representation method is used to extract the latent features of the submodal data, so the noise information in the submodal data is removed. Then, discriminant correlation analysis is used to fuse the submodal data, so the complementary information can be fully utilized. The experimental results indicate the effectiveness of this method.

Effectiveness and safety of pulsatile intravenous insulin therapy for the improvement of respiratory quotient in Chinese patients with diabetes mellitus.

Pulsatile intravenous insulin therapy (PIVIT) is a means of imitating naturally occurring insulin pulses artificially. It is thought to improve carbohydrate metabolism, which can be assessed using the respiratory quotient (RQ). The aim of this present study was to assess the efficacy and safety of PIVIT for the improvement of RQ in Chinese patients with diabetes mellitus (DM). This 12-week, multi-center, prospective, randomized, open-label, parallel-group study involved 110 DM patients (both type 1 and type 2) whose RQ was <0.8. Of these, 53 patients formed the control group, in which standard anti-diabetic therapy was maintained, and 54 patients formed the treatment group, which underwent weekly PIVIT in addition to the administration of standard anti-diabetic therapy. RQ was evaluated monthly in control subjects, and before and after every PIVIT treatment in the treatment group. After weekly PIVIT for 12 weeks, the mean RQ increased from 0.70 to 0.90 in the treatment group, but did not change in the control group. The percentage of subjects reporting adverse events (AEs) was 31.5% (17/54) in the treatment group and 9.43% (5/53) in the control group (P=0.0053). The most frequently reported AE (by 12 subjects) was a gastroenteric reaction when these individuals were receiving 50% glucose during the PIVIT treatment. The majority of AEs were mild and did not interfere with the ongoing treatment. Thus, PIVIT can be viewed as tolerated and effective for the improvement of RQ in Chinese DM patients. This study was retrospectively registered with the Chinese Clinical Trial Registry (http://www.chictr.org.cn) on November 13th 2019 (registration no. ChiCTR1900027510).

[Spontaneous pregnancy in a patient with lymphocytic hypophysitis].

Lymphocytic hypophysitis(LH) is a rare but increasingly recognized autoimmune endocrine condition that causes partial or total hypopituitarism and is often associated with peripartum young women. We here report a 28-year-old patient who had a spontaneous and uneventful pregnancy following LH that had been treated with transspenoidal surgery and followed by anti-inflammatory agent. The woman failed to lactate and developed frontal headaches 3 months after normal delivery of her first child 3 years ago. Lab test showed the reduced concentrations of thyroxine, estradial and cortisol, suggesting hypopituitarism. Magnetic resonance imaging of the brain with contrast was performed and showed a uniformly enhancing pituitary mass with elevated optic chiasm. She underwent transsphenoidal surgery and histological examination of the resected specimen was consistent with lymphocytic hypophysitis. Anti-inflamation was started with prednisolone 40 mg per day because of a recurrence of headache that had completely recovered after surgery and regularly withdrawn to a long term maintenance dose of 10 mg per day. Physiological thyroxine replacement therapy was maintained. Her menstruation was restored without sex hormone replacement after 3 months. Three years after surgery, she got pregnant spontaneously and had normal breastfeeding after delivery. LH did not recur during this peripartum.

Pioglitazone Improved Insulin Sensitivity and First Phase Insulin Secretion Among Obese and Lean People with Diabetes: A Multicenter Clamp Study.

INTRODUCTION: To investigate the effects of pioglitazone (PIO) on insulin resistance and first phase insulin secretion among obese and lean Chinese people with type 2 diabetes mellitus (T2DM). METHODS: Sixty-eight drug-naïve patients with T2DM were treated with PIO for 16 weeks. Before and after the treatment, insulin sensitivity was evaluated by the euglycemic hyperinsulinemic clamp test. Plasma insulin levels at 0, 3, 5, 7, and 10 min during intravenous glucose tolerance test were determined to calculate the first phase insulin secretion and pancreatic ß-cell function. Circulating adiponectin levels were quantified. RESULTS: In both the lean and the obese patients with T2DM, the reduction of HbA1c following the PIO treatment was more than 1% (P < 0.001) and glucose infusion rate, acute insulin response, glucose disposal index, and ß-cell glucose sensitivity increased significantly (P < 0.001). A multiple linear regression analysis showed that the improvements of first phase insulin secretion and insulin sensitivity were independently associated with the changes of HbA1c, but the change of first phase insulin secretion exhibited a higher correlation coefficient (R2 = 0.20, P = 0.001) than the change of insulin sensitivity did (R2 = 0.07, P = 0.040). The PIO treatment led to a significant increase in adiponectin levels only in the obese group (P < 0.05). CONCLUSION: A 16-week treatment of PIO significantly increased insulin sensitivity and ß-cell function in the lean group as well as in the obese group among Chinese T2DM patients, demonstrating that both lean and obese diabetic adults would profit from PIO. TRIAL REGISTRATION: The ChiCTR registry number is ChiCTR-OPC-17011571. FUNDING: Takeda Pharmaceutical Co. Ltd. and Pfizer Pharmaceutical Co. Ltd.

Semi-Supervised SVM With Extended Hidden Features.

Many traditional semi-supervised learning algorithms not only train on the labeled samples but also incorporate the unlabeled samples in the training sets through an automated labeling process such as manifold preserving. If some labeled samples are falsely labeled, the automated labeling process will generally propagate negative impact on the classifier in quite a serious manner. In order to avoid such an error propagating effect, the unlabeled samples should not be directly incorporated into the training sets during the automated labeling strategy. In this paper, a new semi-supervised support vector machine with extended hidden features (SSVM-EHF) is presented to address this issue. According to the maximum margin principle and the minimum integrated squared error between the probability distributions of the labeled and unlabeled samples, the dimensionality of the labeled and unlabeled samples is extended through an orthonormal transformation to generate the corresponding hidden features shared by the labeled and unlabeled samples. After doing so, the last step in the process of training of SSVM-EHF is done only on the labeled samples with their original and hidden features, and the unlabeled samples are no longer explicitly used. Experimental results confirm the effectiveness of the proposed method.

The functional layered organosilica materials prepared with anion surfactant templates.

A novel strategy for the synthesis of layered organosilica is demonstrated. The ionic interaction between the anionic group of a surfactant (sodium dodecyl sulfate) and the cationic organic group of an organosilane (3-aminopropyltrimethoxysilane, ATMS) under acidic conditions was utilized to create a layered organosilica at room temperature. The inorganic part of the organosilica layer was an Si-O hexagonal sheet, and organofunctional groups were alternately arranged on both sides of the sheet. The layered structure of the ATMS organosilica was retained after the removal of the surfactant with chloride anion. The properties of the layered ATMS organosilica were investigated. The layered ATMS-Cl organosilica is stable and possesses a definite layer structure in water or ethanol. Various kinds of anions can be intercalated in the interlayer space of the layered ATMS organosilicas and the layer was expanded dependent on the intercalated anions. The structure of the layered ATMS organosilica was well retained during the intercalation processes.

[The changes in plasma leptin, insulin and proinsulin levels in obese adolescents].

OBJECTIVE: To investigate the metabolic changes in obese adolescents and the relationship between obese adolescents and metabolic syndrome. METHODS: 198 obese adolescents [body mass index (BMI) >/= 25 kg/m(2)] and 78 normal adolescents (BMI 18.5 approximately 23.0 kg/m(2)) were chosen from 2 217 middle school students of 14 approximately 16 years. The levels of serum leptin, insulin, proinsulin, glucose and lipids of these adolescents were measured and compared. RESULTS: (1) There was significant gender difference of serum leptin levels in adolescents of 14 approximately 16 years. The level of serum leptin was higher in female than that in male [(18.53 +/- 1.41) microgram/L vs (6.33 +/- 1.79) microgram/L]. (2) The levels of serum leptin, insulin and proinsulin of obese adolescents were significantly higher than those of normal adolescents [(19.94 +/- 1.91) microgram/L vs (11.27 +/- 2.04) microgram/L, (15.34 +/- 1.66) microIU/L vs (13.17 +/- 1.43) microIU/L and (16.19 +/- 1.64) pmol/L vs (11.79 +/- 1.70) pmol/L respectively]. (3) The levels of blood glucose and triglyceride of obese adolescents were significantly higher than those of normal adolescents [(4.63 +/- 0.50) mmol/L vs (4.13 +/- 0.33) mmol/L and (1.20 +/- 0.56) mmol/L vs (0.90 +/- 0.32) mmol/L respectively], but the levels of serum high-density lipoprotein cholesterol (HDL-C) of obese adolescents were significantly lower than those of normal adolescents [(1.14 +/- 0.24) mmol/L vs (1.38 +/- 0.26) mmol/L]. CONCLUSION: It is suggested that there are leptin resistance, insulin resistance and potential disorders of blood glucose and lipid metabolism in obese adolescents. Our study indicated that adolescent obesity would be related with early occurrence of type 2 diabetes.