Experimental Limits on Solar Reflected Dark Matter with a New Approach on Accelerated-Dark-Matter-Electron Analysis in Semiconductors

Recently a dark matter-electron (DM-electron) paradigm has drawn much attention. Models beyond the standard halo model describing DM accelerated by high energy celestial bodies are under intense examination as well. In this Letter, a velocity components analysis (VCA) method dedicated to swift analysis of accelerated DM-electron interactions via semiconductor detectors is proposed and the first HPGe detector-based accelerated DM-electron analysis is realized. Utilizing the method, the first germanium based constraint on sub-GeV solar reflected DM-electron interaction is presented with the 205.4  kg·day dataset from the CDEX-10 experiment. In the heavy mediator scenario, our result excels in the mass range of 5-15  keV/c^{2}, achieving a 3 orders of magnitude improvement comparing with previous semiconductor experiments. In the light mediator scenario, the strongest laboratory constraint for DM lighter than 0.1  MeV/c^{2} is presented. The result proves the feasibility and demonstrates the vast potential of the VCA technique in future accelerated DM-electron analyses with semiconductor detectors.

EvoAI enables extreme compression and reconstruction of the protein sequence space

Designing proteins with improved functions requires a deep understanding of how sequence and function are related, a vast space that is hard to explore. The ability to efficiently compress this space by identifying functionally important features is extremely valuable. Here, we first establish a method called EvoScan to comprehensively segment and scan the high-fitness sequence space to obtain anchor points that capture its essential features, especially in high dimensions. Our approach is compatible with any biomolecular function that can be coupled to a transcriptional output. We then develop deep learning and large language models to accurately reconstruct the space from these anchors, allowing computational prediction of novel, highly fit sequences without prior homology-derived or structural information. We apply this hybrid experimental-computational method, which we call EvoAI, to a repressor protein and find that only 82 anchors are sufficient to compress the high-fitness sequence space with a compression ratio of 1048. The extreme compressibility of the space informs both applied biomolecular design and understanding of natural evolution.

Development and validation of a preoperative CT-based risk scoring system for predicting recurrence-free survival in patients undergoing curative surgery for gastric cancer

PURPOSE

The objective of this study was to establish and validate a preoperative risk scoring system that incorporated both clinical and computed tomography(CT) variables to predict recurrence-free survival (RFS) in gastric cancer(GC) patients who underwent curative resection.

METHOD

We retrospectively included consecutive patients with surgically confirmed GC who underwent preoperative CT scans between October 2017 and January 2022. Multivariate Cox regression analysis was employed in the derivation set to identify clinical and CT variables associated with RFS and to construct a risk score. This risk score was subsequently validated in an independent test set.

RESULTS

A total of 346 patients were included in the study, with 213 in the derivation set and 133 in the test set. Five variables, namely ctEMVI, ctBorrmann, visceral obesity, sarcopenia, and NLR, were independently associated with RFS. In the test set, the preoperative risk score exhibited a c-index of 0.741, which outperformed the predictive accuracy of pathological tumor staging (c-index of 0.673, p = 0.021) at various time points. The preoperative risk score effectively stratified patients into low and high-risk groups.

CONCLUSION

The developed preoperative risk scoring system demonstrated the ability to predict RFS following curative resection in GC patients.

Study on the diagnostic value of MDCT extramural vascular invasion in preoperative N staging of gastric cancer patients

BACKGROUND

To explore the diagnostic value of multidetector computed tomography (MDCT) extramural vascular invasion (EMVI) in preoperative N Staging of gastric cancer patients.

METHODS

According to the MR-defined EMVI scoring standard of rectal cancer, we developed a 5-point scale scoring system to evaluate the status of CT-detected extramural vascular invasion(ctEMVI), 0-2 points were ctEMVI-negative status, and 3-4 points were positive status for ctEMVI. Patients were divided into ctEMVI positive group and ctEMVI negative group. The correlation between ctEMVI and clinical features was analyzed. Receiver operating characteristic (ROC) curve was used to evaluate the diagnostic efficacy of ctEMVI for pathological metastatic lymph nodes and N staging, The sensitivity, specificity, accuracy, positive predictive value (PPV), and negative predictive value (NPV) of pathological N staging using ctEMVI and short-axis diameter were generated and compared.

RESULTS

The occurrence rate of lymphovascular invasion (LVI) and proportion of tumors with a greatest diameter > 6 cm in the ctEMVI positive group was higher than that in the ctEMVI negative group (P < 0.05). Spearman correlation analysis showed a positive correlation between ctEMVI and LVI, N stage, and tumor size (P < 0.05). For ctEMVI scores ≥ 3,The AUC of ctEMVI for diagnosing lymph node metastasis, N stage ≥ N2, and N3 stage were 0.857, 0.802, and 0.758, respectively. The sensitivity, NPV and accuracy of ctEMVI for diagnosing N stage ≥ N2 were superior to those of short-axis diameter (P < 0.05), while sensitivity, specificity, PPV, NPV, and accuracy of ctEMVI for diagnosing N3 stage were superior to those of short-axis diameter (P < 0.05).

CONCLUSION

ctEMVI has important value in diagnosing metastatic lymph nodes and advanced N staging. As an important imaging marker, ctEMVI can be included in the preoperative imaging evaluation of patients, providing important assistance for clinical guidance and treatment.

Comparison of anal function and quality of life after conformal sphincter preservation operation and intersphincteric resection of very low rectal cancer: a multicenter, retrospective, case-control analysis

PURPOSE

Conformal sphincter preservation operation (CSPO) is a sphincter preservation operation for very low rectal cancers. Compared to intersphincteric resection (ISR), CSPO retains more dentate line and distal rectal wall, and also avoids damaging the nerves in the intersphincteric space. This study aimed to compare the postoperative anal function and quality of life between the CSPO and ISR.

METHOD

Patients with low rectal cancer undergoing CSPO (n = 117) and ISR (n = 66) were included from Changhai and Huashan Hospital, respectively, between 2011 and 2020. A visual analog scale (range 0-10) was utilized to evaluate satisfaction with anal function and quality of life. The anal function was evaluated with Wexner scores and low anterior resection syndrome (LARS) score. Quality of life was evaluated with the EORTC QLQ-C30 and QLQ-CR38.

RESULTS

The CSPO group had more male patients (65.8% vs. 50%, p = 0.042), more preoperative chemoradiotherapy (33.3% vs. 10.6%, p < 0.001), lower tumor position (3.45 ± 1.13 vs. 4.24 ± 0.86 cm, p < 0.001), and more postoperative chemotherapy (65% vs. 13.6%, p < 0.001) compared to the ISR group. In addition, CSPO patients had shorter postoperative stay (6.63 ± 2.53 vs. 7.85 ± 4.73 days, p = 0.003) and comparable stoma reversal rates within 1 year after surgery (92.16% vs. 96.97%, p = 0.318). Multivariable analysis showed that CSPO significantly contributed to higher satisfaction with anal function (beta = 1.752, 95% CI 0.776-2.728) and with quality of life (beta = 1.219, 95% CI 0.374-2.064), but not to Wexner, LARS score, or EORTC QLQ-C30 and QLQ-CR38.

CONCLUSION

CSPO improved the satisfaction with anal function and quality of life but utilized more preoperative chemoradiotherapy. CSPO may be an alternative choice for patients with very low rectal cancers in better physical health and with higher requirements for anal function and quality of life.

[Estimate the population size of transgender women based on the capture-recapture method in Tianjin]

Objective: To investigate the population size of transgender women (TGW) in Tianjin and analyze the characteristics of their sexual behaviors to provide a basis for AIDS prevention and control. Methods: To estimate the population size of TGW in Tianjin using the capture-recapture method. At the same time, an anonymous questionnaire was collected to conduct a multi-factor logistic analysis of the TGW population's sexual behavior. Results: A total of 213 TGW were investigated. Tianjin's estimated TGW population size was 599 (95%CI: 407-792). Multivariate logistic analysis of the use of condoms consistently showed that compared with TGW without regular sex partners, those with regular sex partners had a lower proportion of consistent condom use (aOR=0.44, 95%CI: 0.23-0.82) and had received HIV tests in the last year were more likely to adhere to condom use than those who had not been tested (aOR=2.73, 95%CI: 1.06-6.99). Conclusion: It is necessary to strengthen HIV mobilization testing among the TGW population and their regular sexual partners to improve condom use.

Improved Measurement of the Evolution of the Reactor Antineutrino Flux and Spectrum at Daya Bay

Reactor neutrino experiments play a crucial role in advancing our knowledge of neutrinos. In this Letter, the evolution of the flux and spectrum as a function of the reactor isotopic content is reported in terms of the inverse-beta-decay yield at Daya Bay with 1958 days of data and improved systematic uncertainties. These measurements are compared with two signature model predictions: the Huber-Mueller model based on the conversion method and the SM2018 model based on the summation method. The measured average flux and spectrum, as well as the flux evolution with the ^{239}Pu isotopic fraction, are inconsistent with the predictions of the Huber-Mueller model. In contrast, the SM2018 model is shown to agree with the average flux and its evolution but fails to describe the energy spectrum. Altering the predicted inverse-beta-decay spectrum from ^{239}Pu fission does not improve the agreement with the measurement for either model. The models can be brought into better agreement with the measurements if either the predicted spectrum due to ^{235}U fission is changed or the predicted ^{235}U, ^{238}U, ^{239}Pu, and ^{241}Pu spectra are changed in equal measure.

[Embedded 3D printing of porous silicon orbital implants and its surface modification]

OBJECTIVE

To prepare customized porous silicone orbital implants using embedded 3D printing and assess the effect of surface modification on the properties of the implants.

METHODS

The transparency, fluidity and rheological properties of the supporting media were tested to determine the optimal printing parameters of silicone. The morphological changes of silicone after modification were analyzed by scanning electron microscopy, and the hydrophilicity and hydrophobicity of silicone surface were evaluated by measuring the water contact angle. The compression modulus of porous silicone was measured using compression test. Porcine aortic endothelial cells (PAOECs) were co-cultured with porous silicone scaffolds for 1, 3 and 5 days to test the biocompatibility of silicone. The local inflammatory response to subcutaneous porous silicone implants was evaluated in rats.

RESULTS

The optimal printing parameters of silicone orbital implants were determined as the following: supporting medium 4% (mass ratio), printing pressure 1.0 bar and printing speed 6 mm/s. Scanning electron microscopy showed that the silicone surface was successfully modified with polydopamine and collagen, which significantly improved hydrophilicity of the silicone surface (P < 0.05) without causing significant changes in the compression modulus (P > 0.05). The modified porous silicone scaffold had no obvious cytotoxicity and obviously promoted adhesion and proliferation of PAOECs (P < 0.05). In rats bearing the subcutaneous implants, no obvious inflammation was observed in the local tissue.

CONCLUSION

Poprous silicone orbital implants with uniform pores can be prepared using embedded 3D printing technology, and surface modification obviously improves hydrophilicity and biocompatibility of the silicone implants for potential clinical application.

Cancer-cell-derived fumarate suppresses the anti-tumor capacity of CD8+ T cells in the tumor microenvironment

Metabolic alterations in the microenvironment significantly modulate tumor immunosensitivity, but the underlying mechanisms remain obscure. Here, we report that tumors depleted of fumarate hydratase (FH) exhibit inhibition of functional CD8⁺ T cell activation, expansion, and efficacy, with enhanced malignant proliferative capacity. Mechanistically, FH depletion in tumor cells accumulates fumarate in the tumor interstitial fluid, and increased fumarate can directly succinate ZAP70 at C96 and C102 and abrogate its activity in infiltrating CD8⁺ T cells, resulting in suppressed CD8⁺ T cell activation and anti-tumor immune responses in vitro and in vivo. Additionally, fumarate depletion by increasing FH expression strongly enhances the anti-tumor efficacy of anti-CD19 CAR T cells. Thus, these findings demonstrate a role for fumarate in controlling TCR signaling and suggest that fumarate accumulation in the tumor microenvironment (TME) is a metabolic barrier to CD8⁺ T cell anti-tumor function. And potentially, fumarate depletion could be an important strategy for tumor immunotherapy.

Precision Measurement of Reactor Antineutrino Oscillation at Kilometer-Scale Baselines by Daya Bay

We present a new determination of the smallest neutrino mixing angle θ_{13} and the mass-squared difference Δm_{32}^{2} using a final sample of 5.55×10^{6} inverse beta-decay (IBD) candidates with the final-state neutron captured on gadolinium. This sample is selected from the complete dataset obtained by the Daya Bay reactor neutrino experiment in 3158 days of operation. Compared to the previous Daya Bay results, selection of IBD candidates has been optimized, energy calibration refined, and treatment of backgrounds further improved. The resulting oscillation parameters are sin^{2}2θ_{13}=0.0851±0.0024, Δm_{32}^{2}=(2.466±0.060)×10^{-3}  eV^{2} for the normal mass ordering or Δm_{32}^{2}=-(2.571±0.060)×10^{-3}  eV^{2} for the inverted mass ordering.

Constraints on Sub-GeV Dark Matter-Electron Scattering from the CDEX-10 Experiment

We present improved germanium-based constraints on sub-GeV dark matter via dark matter-electron (χ-e) scattering using the 205.4  kg·day dataset from the CDEX-10 experiment. Using a novel calculation technique, we attain predicted χ-e scattering spectra observable in high-purity germanium detectors. In the heavy mediator scenario, our results achieve 3 orders of magnitude of improvement for m_{χ} larger than 80  MeV/c^{2} compared to previous germanium-based χ-e results. We also present the most stringent χ-e cross-section limit to date among experiments using solid-state detectors for m_{χ} larger than 90  MeV/c^{2} with heavy mediators and m_{χ} larger than 100  MeV/c^{2} with electric dipole coupling. The result proves the feasibility and demonstrates the vast potential of a new χ-e detection method with high-purity germanium detectors in ultralow radioactive background.

Exotic Dark Matter Search with the CDEX-10 Experiment at China's Jinping Underground Laboratory

A search for exotic dark matter (DM) in the sub-GeV mass range has been conducted using 205 kg day data taken from a p-type point contact germanium detector of the CDEX-10 experiment at China's Jinping underground laboratory. New low-mass dark matter searching channels, neutral current fermionic DM absorption (χ+A→ν+A) and DM-nucleus 3→2 scattering (χ+χ+A→ϕ+A), have been analyzed with an energy threshold of 160 eVee. No significant signal was found; thus new limits on the DM-nucleon interaction cross section are set for both models at the sub-GeV DM mass region. A cross section limit for the fermionic DM absorption is set to be 2.5×10^{-46}  cm^{2} (90% C.L.) at DM mass of 10  MeV/c^{2}. For the DM-nucleus 3→2 scattering scenario, limits are extended to DM mass of 5 and 14  MeV/c^{2} for the massless dark photon and bound DM final state, respectively.

First Measurement of High-Energy Reactor Antineutrinos at Daya Bay

This Letter reports the first measurement of high-energy reactor antineutrinos at Daya Bay, with nearly 9000 inverse beta decay candidates in the prompt energy region of 8-12 MeV observed over 1958 days of data collection. A multivariate analysis is used to separate 2500 signal events from background statistically. The hypothesis of no reactor antineutrinos with neutrino energy above 10 MeV is rejected with a significance of 6.2 standard deviations. A 29% antineutrino flux deficit in the prompt energy region of 8-11 MeV is observed compared to a recent model prediction. We provide the unfolded antineutrino spectrum above 7 MeV as a data-based reference for other experiments. This result provides the first direct observation of the production of antineutrinos from several high-Q_{β} isotopes in commercial reactors.

Identifying a Feasible Transition Pathway between Two Conformational States for a Protein

Proteins usually need to transit between different conformational states to fulfill their biological functions. In the mechanistic study of such transition processes by molecular dynamics simulations, identification of the minimum free energy path (MFEP) can substantially reduce the sampling space, thus enabling rigorous thermodynamic evaluation of the process. Conventionally, the MFEP is derived by iterative local optimization from an initial path, which is typically generated by simple brute force techniques like the targeted molecular dynamics (tMD). Therefore, the quality of the initial path determines the successfulness of MFEP estimation. In this work, we propose a method to improve derivation of the initial path. Through iterative relaxation-biasing simulations in a bidirectional manner, this method can construct a feasible transition pathway connecting two known states for a protein. Evaluation on small, fast-folding proteins against long equilibrium trajectories supports the good sampling efficiency of our method. When applied to larger proteins including the catalytic domain of human c-Src kinase as well as the converter domain of myosin VI, the paths generated by our method deviate significantly from those computed with the generic tMD approach. More importantly, free energy profiles and intermediate states obtained from our paths exhibit remarkable improvements over those from tMD paths with respect to both physical rationality and consistency with a priori knowledge.

Protein design via deep learning

Proteins with desired functions and properties are important in fields like nanotechnology and biomedicine. De novo protein design enables the production of previously unseen proteins from the ground up and is believed as a key point for handling real social challenges. Recent introduction of deep learning into design methods exhibits a transformative influence and is expected to represent a promising and exciting future direction. In this review, we retrospect the major aspects of current advances in deep-learning-based design procedures and illustrate their novelty in comparison with conventional knowledge-based approaches through noticeable cases. We not only describe deep learning developments in structure-based protein design and direct sequence design, but also highlight recent applications of deep reinforcement learning in protein design. The future perspectives on design goals, challenges and opportunities are also comprehensively discussed.

Joint Determination of Reactor Antineutrino Spectra from ^{235}U and ^{239}Pu Fission by Daya Bay and PROSPECT

A joint determination of the reactor antineutrino spectra resulting from the fission of ^{235}U and ^{239}Pu has been carried out by the Daya Bay and PROSPECT Collaborations. This Letter reports the level of consistency of ^{235}U spectrum measurements from the two experiments and presents new results from a joint analysis of both data sets. The measurements are found to be consistent. The combined analysis reduces the degeneracy between the dominant ^{235}U and ^{239}Pu isotopes and improves the uncertainty of the ^{235}U spectral shape to about 3%. The ^{235}U and ^{239}Pu antineutrino energy spectra are unfolded from the jointly deconvolved reactor spectra using the Wiener-SVD unfolding method, providing a data-based reference for other reactor antineutrino experiments and other applications. This is the first measurement of the ^{235}U and ^{239}Pu spectra based on the combination of experiments at low- and highly enriched uranium reactors.

BERT-Kcr: prediction of lysine crotonylation sites by a transfer learning method with pre-trained BERT models

MOTIVATION

As one of the most important post-translational modifications (PTMs), protein lysine crotonylation (Kcr) has attracted wide attention, which involves in important physiological activities, such as cell differentiation and metabolism. However, experimental methods are expensive and time-consuming for Kcr identification. Instead, computational methods can predict Kcr sites in silico with high efficiency and low cost.

RESULTS

In this study, we proposed a novel predictor, BERT-Kcr, for protein Kcr sites prediction, which was developed by using a transfer learning method with pre-trained bidirectional encoder representations from transformers (BERT) models. These models were originally used for natural language processing (NLP) tasks, such as sentence classification. Here, we transferred each amino acid into a word as the input information to the pre-trained BERT model. The features encoded by BERT were extracted and then fed to a BiLSTM network to build our final model. Compared with the models built by other machine learning and deep learning classifiers, BERT-Kcr achieved the best performance with AUROC of 0.983 for 10-fold cross validation. Further evaluation on the independent test set indicates that BERT-Kcr outperforms the state-of-the-art model Deep-Kcr with an improvement of about 5% for AUROC. The results of our experiment indicate that the direct use of sequence information and advanced pre-trained models of NLP could be an effective way for identifying PTM sites of proteins.

AVAILABILITY AND IMPLEMENTATION

The BERT-Kcr model is publicly available on http://zhulab.org.cn/BERT-Kcr_models/.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

[Clinical and genetic spectrum of SCN2A gene associated epilepsy and episodic ataxia]

Objective: To explore the clinical manifestations and genetic characteristics of patients with epilepsy and episodic ataxia caused by SCN2A gene variation. Methods: The clinical data of seizure manifestation, imaging examination and genetic results of 5 patients with epilepsy and (or) episodic ataxia because of SCN2A gene variation admitted to the Department of Pediatrics, the Third Affiliated Hospital of Zhengzhou University from July 2017 to January 2021 were analyzed retrospectively. Results: Among 5 patients, 4 were female and 1 was male. The onset age of epilepsy ranged from 4 days to 8 months. There were 2 cases of benign neonatal or infantile epilepsy and 3 cases of epileptic encephalopathy, in whom 1 case had development retardation,1 case transformed from West syndrome to infantile spasm and another one transformed from infantile spasm to Lennox-Gastaut syndrome. One case of benign neonatal-infantile epilepsy was characterized by neonatal onset seizures and episodic ataxia developed at the age of 78 months. Electroencephalograms at first visit of 5 cases showed that 2 cases were normal, 1 case had focal epileptic discharge, and 2 cases had multi-focal abnormal discharge with peak arrhythmia. The brain magnetic resonance imaging (MRI) of 3 cases were nomal, 1 case was abnormal (brain atrophy with decreased white matter) and the results of 1 case was unknown. The follow-up time ranged from 17 months to 89 months. Four cases of epilepsy were controlled and 1 case died at 2 years of age. Two cases had normal intelligence and motor development, 2 had moderate to severe intelligence retardation and motor critical state, and 1 had moderate to severe intelligence and motor development retardation. SCN2A gene variations were identified in all cases. There were 4 missense variations and 1 frameshift variation. Three variations had not been reported so far, including c.4906A>G,c.3643G>T,c.638delT. Conclusions: Variations in SCN2A gene can cause benign neonatal or infantile epilepsy and epileptic encephalopathy. Some children develop episodic ataxia with growing age. The variation of SCN2A gene is mainly missense variation.

The Relationship between Dietary Copper intake and Telomere Length in Hypertension

BACKGROUND

More indications proved that diet might be involved in the telomere length, a marker of biological aging and chronic diseases. Copper is widely viewed as one of the essential elements in the diet. Therefore, this study aimed to evaluate the relationship between telomere length and dietary copper intake in hypertension and provide a basis for guiding dietary copper intake in patients with hypertension.

METHODS

The data was collected from the National Health and Nutrition Examination Survey (NHANES) in 1999-2000 and 2001-2002. The relevance between telomere length and dietary copper intake in hypertension is assessed using a multivariable linear regression model.

RESULTS

We gathered 1,867 participants with hypertension with assessed telomere length and dietary copper intake. We found that one unit increasing log-transformed dietary copper intake in hypertension was significantly associated with longer telomere length base pair (bp) (β = 112.20, 95% confidence interval [CI]: 5.48, 218.92), after controlling for covariates, including age, sex, ethnicity, body mass index (BMI), physical activity, and taking medication for hypertension. For the age group, we found that one unit increasing log-transformed dietary copper in hypertension was associated with longer telomere length (β = 237.95, 95% CI: 114.39, 361.51) in the age group >45 years. The grouping was based on whether the participants take medication for hypertension. We found that one unit increasing log-transformed dietary copper in hypertension was associated with longer telomere length (β = 116.47, 95% CI: 0.72, 232.21) in the group that takes medication for hypertension.

CONCLUSIONS

This study demonstrates that dietary copper intake was associated with longer telomere length in patients with hypertension, which provides evidence for guiding dietary copper intake in patients with hypertension. However, further studies are needed to evaluate the effect of copper supplementation on telomere length in patients with hypertension in well-designed random control studies and prospective studies.

Portable fluid circuit device containing printed silicone microvessels as a training aid for arterial microanastomosis

Anastomosis of the microvessels requires high-level skills and extensive basic training. This study was performed to introduce and evaluate an inexpensive laboratory device as a training aid. Micro-tubes of 0.8 mm inner diameter and 0.5/0.8 mm wall thickness mimicking human vein/artery were printed from a silicon-containing hydrogel using three-dimensional printing technology. The hydrogel components are optimized to render the printed tubes biomechanical features resembling the blood vessels of a living organism. These artificial vessels were connected to a pump for fluid flow, simulating the blood circulation. Forty medical interns were assigned to two equal groups. The 20 interns in group A practiced anastomosis using the training aid for a total of 10 hours over 5 days. The 20 interns in group B practiced anastomosis using the traditional gum pieces and silicone tubes. Then, all interns performed anastomosis on rat carotid arteries, and their performance was scored by a team of five experienced maxillofacial surgeons. The average success score and time required for anastomosis were compared between the two groups. The mean success score of group A was significantly higher than that of group B (0.83 ± 0.12 vs 0.64 ± 0.10, P < 0.001). The mean anastomosis time of group A was significantly shorter than that of group B (10.2 ± 1.1 vs 17.2 ± 1.4 minutes, P < 0.001). This training device for vessel microanastomosis is an inexpensive, practical, and effective tool for use in laboratories and also reduces the use of animals.

Exploring the Regulatory Function of the N-terminal Domain of SARS-CoV-2 Spike Protein through Molecular Dynamics Simulation

SARS-CoV-2 is what has caused the COVID-19 pandemic. Early viral infection is mediated by the SARS-CoV-2 homo-trimeric Spike (S) protein with its receptor binding domains (RBDs) in the receptor-accessible state. Molecular dynamics simulation on the S protein with a focus on the function of its N-terminal domains (NTDs) is performed. The study reveals that the NTD acts as a "wedge" and plays a crucial regulatory role in the conformational changes of the S protein. The complete RBD structural transition is allowed only when the neighboring NTD that typically prohibits the RBD's movements as a wedge detaches and swings away. Based on this NTD "wedge" model, it is proposed that the NTD-RBD interface should be a potential drug target.

Transcriptome profiling reveals morphogenesis-related candidate genes and pathways in the chick embryonic small intestine

1. A better understanding of intestinal development is essential for the intestinal health of poultry. Intestinal villification starts on embryo day E15 and is generally completed before hatching (E21). The development of lymphoid organs in the intestine starts during embryogenesis. However, transcriptional information on the processing of intestinal morphogenesis and immune development during chick embryogenesis is limited.2. In this work, RNA-sequencing was performed using 12 biological replicates to investigate Hy-Line brown chick embryonic small intestinal transcription at E15 and E21. Differentially expressed genes (DEGs) between E15 and E21 were identified. GO and KEGG enrichment analyses, based on the DEGs, were performed to identify key GO terms in the biological process category and key KEGG pathways. PPI networks were constructed based on the DEGs in the key pathways to screen hub genes. The embryonic small intestinal morphology and IgA distribution were observed by histological processing. The serum levels of IgA and lysozyme were measured by ELISA.3. A total of 76.38 Gb of high-quality RNA-sequencing data were generated and uploaded. A total of 2,676 DEGs, between E15 and E21, were identified. Structural development and villification of the small intestine at E15 tended to proceed via the expression of nervous system development-related genes. A combination of the histological and serological results with the transcriptome data indicated that the identified genes and pathways may be strong candidates for intestinal morphogenesis-regulation.4. The small intestine appears to have developed a relatively complete morphology and transport, metabolism, digestion and immunity functions by E21. This work provided a transcriptome profile of the chick embryonic small intestine and provided insights into the intestinal development and health of poultry.

[Cost-effectiveness analysis of quadrivalent influenza vaccination for older adults aged 60 and above in mainland China]

Objective: To evaluate the cost-effectiveness of government fully-funded quadrivalent influenza vaccination (QIV) program for older adults aged 60 and above in mainland China. Methods: Based on decision tree model in the previous research on the cost-effectiveness analysis of TIV immunization, we extended the structure of model and updated the key parameters such as influenza patients' healthcare seeking behavior, vaccine cost, vaccine coverage and vaccine efficacy/effectiveness to estimate influenza-associated outpatient consultations, hospitalizations, respiratory disease excess mortality and quality-adjusted life years (QALY) between the QIV and no vaccination or TIV program. And incremental cost and incremental cost-effectiveness ratio (ICER) were evaluated between the QIV and no vaccination or TIV program from the societal perspective. The time frame of the study is one year. All costs were adjusted to 2019 using the consumer price index. Results: Comparing the fully-funded QIV and no vaccination or TIV for older adults aged 60 and above is separately expected to prevent 45 070 or 2 718 influenza-associated influenza-like illness (ILI) outpatients, 21 451 or 1 294 influenza-associated severe acute respiratory infection (SARI) hospitalizations, 19 346 or 1 167 influenza-associated respiratory excess deaths and avoid 155 234 or 9 363 QALY loss each year. Compared with no vaccination, introducing QIV into National Immunization Program (NIP) is expected to increase the cost of 11.71 billion yuan from the societal perspective. The incremental cost per QALY gained between QIV and no vaccination was 75 325 yuan per QALY, which is higher than willingness-to-pay (WTP) threshold (one-fold gross domestic product per capita is considered as WTP: 70 892 yuan) and means no cost effective. Introducing QIV rather than TIV into NIP will cost 7.98 billion yuan from the societal perspective and the ICER was 852.54 thousand yuan per QALY which is much higher than WTP and means no cost effective as well. The threshold of vaccination cost between QIV and no vaccination or TIV should no more than 113.41 or 6.83 yuan when the two comparators' scenarios above are all cost effective. Conclusion: Under the condition of current vaccine effectiveness and vaccine cost, comparing fully-funded QIV with no or TIV vaccination program is not cost effective for people aged 60 years or older.

SAMF: a Self-adaptive Protein Modeling Framework

MOTIVATION

Gradient descent-based protein modeling is a popular protein structure prediction approach that takes as input the predicted inter-residue distances and other necessary constraints and folds protein structures by minimizing protein-specific energy potentials. The constraints from multiple predicted protein properties provide redundant and sometime conflicting information that can trap the optimization process into local minima and impairs the modeling efficiency.

RESULTS

To address these issues, we developed a self-adaptive protein modeling framework, SAMF. It eliminates redundancy of constraints and resolves conflicts, folds protein structures in an iterative way, and picks up the best structures by a deep quality analysis system. Without a large amount of complicated domain knowledge and numerous patches as barriers, SAMF achieves the state-of-the-art performance by exploiting the power of cutting-edge techniques of deep learning. SAMF has a modular design and can be easily customized and extended. As the quality of input constraints is ever growing, the superiority of SAMF will be amplified over time.

AVAILABILITY

The source code and data for reproducing the results is available at https://msracb.blob.core.windows.net/pub/psp/SAMF.zip.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Prevalence of lumbosacral transitional vertebrae in dogs in Berlin

Lumbosacral transitional vertebrae (LTV) are abnormally formed vertebrae of congenital origin. Dogs with LTV are predisposed to premature degeneration of the lumbosacral spine and hip dysplasia due to a weakened sacroiliac attachment. Moreover, LTV has been discussed as a cause of cauda equina syndrome. To date, LTV remain poorly understood and a diagnostic standard is yet to be established. This study examines prevalence, types and breed predispositions for LTV in the canine population in Berlin. The diagnostic value of laterolateral radiographs of the lumbosacral region, in addition to ventrodorsal radiographs, was also evaluated. The prevalence of LTV was assessed by reviewing ventrodorsal pelvic radiographs of 1030 dogs. LTV were detected in 95 (9.2%) dogs. The prevalence was higher in Pugs (63.6%) and Jack Russel Terriers (27.6%) than in the other breeds. The most common type of LTV was type II (37.9%), showing separation of the first sacral segment from the sacrum, the presence of a rudi-mentary intervertebral space between the first sacral segment and the rest of the sacrum, and symmetrically formed transverse processes. Laterolateral radiographs were available for 66 of 95 dogs with LTV and provided evidence of a rudimentary intervertebral disc space between the first and second sacral vertebrae in all cases of LTV type II and III (100%). The results of this study contribute to a better understanding of the condition. Furthermore, they demonstrate that laterolateral radiographs are a valuable addition to standard ventrodorsal radiographs and should be included in routine LTV screening protocols to provide a complete evaluation.

Molecular Characterisation, Tissue Distribution, and Expression Profiling of the Cathepsin B Gene during Ovarian Follicle Development in Geese

1. Although there is evidence that Cathepsin B (CTSB) regulates the degradation and absorption of yolk precursors during avian ovarian follicle development, nothing is known about its molecular characteristics, tissue distribution or expression profiles in goose ovarian follicular compartments.2. The intact 1023 bp coding sequence of the goose CTSB gene was obtained for the first time. It encoded a polypeptide of 340 amino acids (AA) containing two conserved functional domains (i.e., Propeptide_C1 and Peptidase_C1A_Cathpsin B) and three active amino acid residues (+108, +279, and +299). Both the nucleotide and AA sequences of goose CTSB gene showed more than 90% similarity with its respective homologs from other avian species.3. The qRT-PCR results showed that CTSB mRNA was ubiquitously expressed in all examined goose tissues, with moderate to high levels in the reproductive organs including the ovarian stroma and oviduct.4. Expression of goose CTSB mRNA in the granulosa layers increased gradually from the 2-4 mm F5 follicles but declined to relatively low levels in the F4-F1 follicles while remaining statistically unchanged in the theca layers throughout follicle development.5. High sequence similarity of goose CTSB gene to other avian species suggested functional conservation of avian CTSB genes, and its fluctuating levels in the granulosa layers may be associated with the orderly progression of goose follicle development. These data laid a foundation for further elucidating the role of CTSB in the avian ovary.

RDb2C2: an improved method to identify the residue-residue pairing in β strands

Background

Despite the great advance of protein structure prediction, accurate prediction of the structures of mainly β proteins is still highly challenging, but could be assisted by the knowledge of residue-residue pairing in β strands. Previously, we proposed a ridge-detection-based algorithm RDb₂C that adopted a multi-stage random forest framework to predict the β-β pairing given the amino acid sequence of a protein.

Results

In this work, we developed a second version of this algorithm, RDb₂C2, by employing the residual neural network to further enhance the prediction accuracy. In the benchmark test, this new algorithm improves the F1-score by > 10 percentage points, reaching impressively high values of ~ 72% and ~ 73% in the BetaSheet916 and BetaSheet1452 sets, respectively.

Conclusion

Our new method promotes the prediction accuracy of β-β pairing to a new level and the prediction results could better assist the structure modeling of mainly β proteins. We prepared an online server of RDb₂C2 at http://structpred.life.tsinghua.edu.cn/rdb2c2.html.

Development of an immunocompetent mouse model susceptible to Cryptosporidium tyzzeri infection

AIMS

Immunocompromised mice are extensively used in the screening of vaccines and drugs for Cryptosporidium, but this study model does not reflect the real status of infection in immunocompetent animals. This study aimed to provide an optimized animal model for future studies of Cryptosporidium vaccine.

METHODS AND RESULTS

Three mouse strains (ICR, BALB/c and KM) with or without immunosuppression were compared after challenge with Cryptosporidium tyzzeri (C tyzzeri). The results indicated that ICR mice shed a greater number of faecal oocysts (20 346 ± 203 oocysts/g) compared with BALB/c (2077 ± 142 oocysts/g) and KM mice (3207 ± 431 oocysts/g) after experimental infection with C tyzzeri (P < .001). However, ICR mouse model is uniquely effective for C tyzzeri, not for other Cryptosporidium spp. such as C parvum. ICR mice were then used to determine the immunoreactions and immunoprotection of P23-DNA vaccine (pVAX1-P23) to C tyzzeri experimental infection. The results showed that a significant increase in anti-P23 antibody levels was induced by the pVAX1-P23 vaccine. Compared to pVAX1, TB and blank control mice, pVAX1-P23 immunized mice produced specific spleen cell proliferation as well as enhanced IL-5, IL-12p70 and IFN-γ production in sera. After challenge with 5 × 10⁶ C tyzzeri oocysts, the oocyst shedding of the pVAX1-P23 immunized group was reduced by 69.94% comparing to the infection control.

CONCLUSION

These results provide an optimized animal model for the study of prophylactic vaccines and this model might be applied to other candidates against Cryptosporidium, not only for pVAX1-P23.

Predicting the Real-Valued Inter-Residue Distances for Proteins

Predicting protein structure from the amino acid sequence has been a challenge with theoretical and practical significance in biophysics. Despite the recent progresses elicited by improved inter-residue contact prediction, contact-based structure prediction has gradually reached the performance ceiling. New methods have been proposed to predict the inter-residue distance, but unanimously by simplifying the real-valued distance prediction into a multiclass classification problem. Here, a lightweight regression-based distance prediction method is shown, which adopts the generative adversarial network to capture the delicate geometric relationship between residue pairs and thus could predict the continuous, real-valued inter-residue distance rapidly and satisfactorily. The predicted residue distance map allows quick structure modeling by the CNS suite, and the constructed models approach the same level of quality as the other state-of-the-art protein structure prediction methods when tested on CASP13 targets. Moreover, this method can be used directly for the structure prediction of membrane proteins without transfer learning.

Improved Constraints on Sterile Neutrino Mixing from Disappearance Searches in the MINOS, MINOS+, Daya Bay, and Bugey-3 Experiments

Searches for electron antineutrino, muon neutrino, and muon antineutrino disappearance driven by sterile neutrino mixing have been carried out by the Daya Bay and MINOS+ collaborations. This Letter presents the combined results of these searches, along with exclusion results from the Bugey-3 reactor experiment, framed in a minimally extended four-neutrino scenario. Significantly improved constraints on the θ_{μe} mixing angle are derived that constitute the most constraining limits to date over five orders of magnitude in the mass-squared splitting Δm_{41}^{2}, excluding the 90% C.L. sterile-neutrino parameter space allowed by the LSND and MiniBooNE observations at 90% CL_{s} for Δm_{41}^{2}<13  eV^{2}. Furthermore, the LSND and MiniBooNE 99% C.L. allowed regions are excluded at 99% CL_{s} for Δm_{41}^{2}<1.6 eV^{2}.

MiR-24 alleviates cardiomyocyte apoptosis after myocardial infarction via targeting BIM

Since this article has been suspected of research misconduct and the corresponding authors did not respond to our request to prove originality of data and figures, "MiR-24 alleviates cardiomyocyte apoptosis after myocardial infarction via targeting BIM, by L.-J. Pan, X. Wang, Y. Ling, H. Gong, published in Eur Rev Med Pharmacol Sci 2017; 21 (13): 3088-3097-PMID: 28742197" has been withdrawn. The Publisher apologizes for any inconvenience this may cause. https://www.europeanreview.org/article/13100.

Frontier Expansion Sampling: A Method to Accelerate Conformational Search by Identifying Novel Seed Structures for Restart

Traditional molecular dynamics (MD) simulations have difficulties in tracking the slow molecular motions, at least partially due to the waste of sampling in already sampled regions. Here, we proposed a new enhanced sampling method, frontier expansion sampling (FEXS), to improve the sampling efficiency of molecular simulations by iteratively selecting seed structures diversely distributed at the "frontier" of an already sampled region to initiate new simulations. Different from other enhanced sampling methods, FEXS identifies the "frontier" seeds by integrating the Gaussian mixture model and the convex hull algorithm, which effectively improves the structural variation among the selected seeds and thus the descendant simulations. Validation in three protein systems, including the folding of chignolin, open-to-closed transition of maltodextrin binding protein, and internal conformational change of bovine pancreatic trypsin inhibitor, confirmed the effectiveness of this novel method in enhancing the sampling of conventional MD simulations to observe the large-scale protein conformational changes. When compared with other enhanced sampling methods like the structural dissimilarity sampling (SDS), FEXS reached at least the same level of sampling efficiency but was capable of providing complementary information in the three tested protein systems.

Direct Detection Constraints on Dark Photons with the CDEX-10 Experiment at the China Jinping Underground Laboratory

We report constraints on the dark photon effective kinetic mixing parameter (κ) with data taken from two p-type point-contact germanium detectors of the CDEX-10 experiment at the China Jinping Underground Laboratory. The 90% confidence level upper limits on κ of solar dark photon from 205.4 kg-day exposure are derived, probing new parameter space with masses (m_{V}) from 10 to 300  eV/c^{2} in direct detection experiments. Considering dark photon as the cosmological dark matter, limits at 90% confidence level with m_{V} from 0.1 to 4.0  keV/c^{2} are set from 449.6 kg-day data, with a minimum of κ=1.3×10^{-15} at m_{V}=200  eV/c^{2}.

DeepCPI: A Deep Learning-based Framework for Large-scale in silico Drug Screening

Accurate identification of compound–protein interactions (CPIs) in silico may deepen our understanding of the underlying mechanisms of drug action and thus remarkably facilitate drug discovery and development. Conventional similarity- or docking-based computational methods for predicting CPIs rarely exploit latent features from currently available large-scale unlabeled compound and protein data and often limit their usage to relatively small-scale datasets. In the present study, we propose DeepCPI, a novel general and scalable computational framework that combines effective feature embedding (a technique of representation learning) with powerful deep learning methods to accurately predict CPIs at a large scale. DeepCPI automatically learns the implicit yet expressive low-dimensional features of compounds and proteins from a massive amount of unlabeled data. Evaluations of the measured CPIs in large-scale databases, such as ChEMBL and BindingDB, as well as of the known drug–target interactions from DrugBank, demonstrated the superior predictive performance of DeepCPI. Furthermore, several interactions among small-molecule compounds and three G protein-coupled receptor targets (glucagon-like peptide-1 receptor, glucagon receptor, and vasoactive intestinal peptide receptor) predicted using DeepCPI were experimentally validated. The present study suggests that DeepCPI is a useful and powerful tool for drug discovery and repositioning. The source code of DeepCPI can be downloaded from https://github.com/FangpingWan/DeepCPI.

Search for Light Weakly-Interacting-Massive-Particle Dark Matter by Annual Modulation Analysis with a Point-Contact Germanium Detector at the China Jinping Underground Laboratory

We present results on light weakly interacting massive particle (WIMP) searches with annual modulation (AM) analysis on data from a 1-kg mass p-type point-contact germanium detector of the CDEX-1B experiment at the China Jinping Underground Laboratory. Datasets with a total live time of 3.2 yr within a 4.2-yr span are analyzed with analysis threshold of 250 eVee. Limits on WIMP-nucleus (χ-N) spin-independent cross sections as function of WIMP mass (m_{χ}) at 90% confidence level (C.L.) are derived using the dark matter halo model. Within the context of the standard halo model, the 90% C.L. allowed regions implied by the DAMA/LIBRA and CoGeNT AM-based analysis are excluded at >99.99% and 98% C.L., respectively. These results correspond to the best sensitivity at m_{χ}<6  GeV/c^{2} among WIMP AM measurements to date.

Prediction of lumbar vertebral strength of elderly men based on quantitative computed tomography images using machine learning

The parameters extracted from quantitative computed tomography (QCT) images were used to predict vertebral strength through machine learning models, and the highly accurate prediction indicated that it may be a promising approach to assess fracture risk in clinics.

INTRODUCTION

Vertebral fracture is common in elderly populations. The main factor contributing to vertebral fracture is the reduced vertebral strength. This study aimed to predict vertebral strength based on clinical QCT images by using machine learning.

METHODS

Eighty subjects with QCT data of lumbar spine were randomly selected from the MrOS cohorts. L1 vertebral strengths were computed by QCT-based finite element analysis. A total of 58 features of each L1 vertebral body were extracted from QCT images, including grayscale distribution, grayscale values of 39 partitioned regions, BMD_QCT, structural rigidity, axial rigidity, and BMD_QCTA_min. Feature selection and dimensionality reduction were used to simplify the 58 features. General regression neural network and support vector regression models were developed to predict vertebral strength. Performance of prediction models was quantified by the mean squared error, the coefficient of determination, the mean bias, and the SD of bias.

RESULTS

The 58 parameters were simplified to five features (grayscale value of the 60% percentile, grayscale values of three specific partitioned regions, and BMD_QCTA_min) and nine principal components (PCs). High accuracy was achieved by using the five features or the nine PCs to predict vertebral strength.

CONCLUSIONS

This study provided an effective approach to predict vertebral strength and showed that it may have great potential in clinical applications for noninvasive assessment of vertebral fracture risk.

Constraints on Spin-Independent Nucleus Scattering with sub-GeV Weakly Interacting Massive Particle Dark Matter from the CDEX-1B Experiment at the China Jinping Underground Laboratory

We report results on the searches of weakly interacting massive particles (WIMPs) with sub-GeV masses (m_{χ}) via WIMP-nucleus spin-independent scattering with Migdal effect incorporated. Analysis on time-integrated (TI) and annual modulation (AM) effects on CDEX-1B data are performed, with 737.1 kg day exposure and 160 eVee threshold for TI analysis, and 1107.5 kg day exposure and 250 eVee threshold for AM analysis. The sensitive windows in m_{χ} are expanded by an order of magnitude to lower DM masses with Migdal effect incorporated. New limits on σ_{χN}^{SI} at 90% confidence level are derived as 2×10^{-32}∼7×10^{-35}  cm^{2} for TI analysis at m_{χ}∼50-180  MeV/c^{2}, and 3×10^{-32}∼9×10^{-38}  cm^{2} for AM analysis at m_{χ}∼75  MeV/c^{2}-3.0  GeV/c^{2}.

Artificial neural network modelling for organic and total nitrogen removal of aerobic granulation under steady-state condition

Aerobic granulation is a recent technology with high level of complexity and sensitivity to environmental and operational conditions. Artificial neural networks (ANNs), computational tools capable of describing complex non-linear systems, are the best fit to simulate aerobic granular bioreactors. In this study, two feedforward backpropagation ANN models were developed to predict chemical oxygen demand (Model I) and total nitrogen removal efficiencies (Model II) of aerobic granulation technology under steady-state condition. Fundamentals of ANN models and the steps to create them were briefly reviewed. The models were respectively fed with 205 and 136 data points collected from laboratory-, pilot-, and full-scale studies on aerobic granulation technology reported in the literature. Initially, 60%, 20%, and 20%, and 80%, 10%, and 10% of the points in the corresponding datasets were randomly chosen and used for training, testing, and validation of Model I, and Model II, respectively. Overall coefficient of determination (R²) value and mean squared error (MSE) of the two models were initially 0.49 and 15.5, and 0.37 and 408, respectively. To improve the model performance, two data division methods were used. While one method is generic and potentially applicable to other fields, the other can only be applied to modelling the performance of aerobic granular reactors. R² value and MSE were improved to 0.90 and 2.54, and 0.81 and 121.56, respectively, after applying the new data division methods. The results demonstrated that ANN-based models were capable simulation approach to predict a complicated process like aerobic granulation.

Using latent class analysis to identify money boys at highest risk of HIV infection

OBJECTIVES

Limited research has been conducted to investigate the characteristics of money boys (MBs) in China. This study was aimed to identify the subgroups of MBs based on sexual behaviors, Net-based venue sex-seeking, and substance abuse.

STUDY DESIGN

Cross-sectional study.

METHODS

Convenience sampling was used to recruit MBs from December 2014 to June 2015 in Tianjin, China. Face-to-face interviews were conducted for 330 MBs, and trained interviewers collected data.

RESULTS

The laboratory-confirmed human immunodeficiency virus (HIV)-positive rate was 11.52% among 330 MBs. Four classes were identified through latent class analysis (LCA) method: 'relatively safe behavior' group, 'higher sexual risk' group, 'multiple sexual-partners' group, and 'unprotected sex and substance abuse' group, and there is a significant difference based on the HIV status. Significant differences were found in original residence, monthly income, duration in sex trade, employment, history of sexually transmitted infection (STI), HIV testing, knowledge of free antiviral treatment policy, and awareness of free AIDS testing between the four latent classes (P < 0.05). MBs who used Net-based venues to seek sexual partners; who have inconsistent condom use, substance abuse, a longer duration in sex trade, multiple sexual clients, and multiple anal sex; and who were full-time employed had the highest risk of HIV infection.

CONCLUSIONS

The utility of LCA to identify subgroups based on risky behaviors attributes to formulating targeted intervention strategy.

Extraction of the ^{235}U and ^{239}Pu Antineutrino Spectra at Daya Bay

This Letter reports the first extraction of individual antineutrino spectra from ^{235}U and ^{239}Pu fission and an improved measurement of the prompt energy spectrum of reactor antineutrinos at Daya Bay. The analysis uses 3.5×10^{6} inverse beta-decay candidates in four near antineutrino detectors in 1958 days. The individual antineutrino spectra of the two dominant isotopes, ^{235}U and ^{239}Pu, are extracted using the evolution of the prompt spectrum as a function of the isotope fission fractions. In the energy window of 4-6 MeV, a 7% (9%) excess of events is observed for the ^{235}U (^{239}Pu) spectrum compared with the normalized Huber-Mueller model prediction. The significance of discrepancy is 4.0σ for ^{235}U spectral shape compared with the Huber-Mueller model prediction. The shape of the measured inverse beta-decay prompt energy spectrum disagrees with the prediction of the Huber-Mueller model at 5.3σ. In the energy range of 4-6 MeV, a maximal local discrepancy of 6.3σ is observed.

[The characteristics of recent HIV-1 infection and associated factors in Tianjin]

The newly reported HIV infected cases was collected, and HIV blood samples were detected to identify recent HIV infection in Tianjin during 2008-2015. Factors associated with HIV-1 infection were analyzed by the univariate and multivariate unconditional logistic regression. The recent HIV-1 infection proportion of homosexuals increased from 37.70% in 2008 to 83.68% in 2015. Those cases who aged ≤30 years (OR=1.53, 95%CI: 1.30-1.79), in han ethnic group (OR=1.40, 95%CI: 1.02-1.91), students (OR=1.79, 95%CI: 1.28-2.51) were more likely to be recent infected. The cases who had a high school education (OR=1.28, 95%CI: 1.05-1.56) or collage education (OR=1.23, 95%CI: 1.00-1.50) were more likely to be recent infected than those who had a primary school education. Compared with patients identified by hospitals, the recent HIV infections were more likely to be found through voluntary counseling and testing (VCT), STD outpatients, men who have sex with men (MSM) investigation and unpaid blood donors. Homosexual transmission has become the major route of HIV-1 recent infection in Tianjin.