Molecular characterization and zoonotic potential of Cryptosporidium spp. and Giardia duodenalis in humans and domestic animals in Heilongjiang Province, China.

BACKGROUND: Cryptosporidiosis and giardiasis are significant parasitic diseases shared between humans and domestic animals. Due to the close contact between humans and domestic animals in rural areas, it is important to consider the potential transmission of zoonotic parasites from infected domestic animals to humans. This investigation aimed to determine the prevalence and molecular characteristics of Cryptosporidium spp. and Giardia duodenalis in domestic animals and villagers. METHODS: A total of 116 fecal samples from villagers and 686 fecal samples from domestic animals in Heilongjiang Province, China, were analyzed for two parasites using nested polymerase chain reaction (PCR) targeting various genetic loci and DNA sequence analysis of the PCR products. RESULTS: By sequence analysis of the SSU rRNA gene, the prevalence of Cryptosporidium in humans was 0.9% (1/116), with one species of C. parvum (n = 1) detected; among domestic animals, the prevalence was 2.6% (18/686), with five species identified: C. suis (n = 7) and C. scrofarum (n = 7) in pigs, C. meleagridis (n = 1) in chickens, C. andersoni (n = 1) in cattle, and C. canis (n = 2) in foxes. C. parvum and C. canis were further subtyped as IIdA19G1 and XXa4 on the basis of gp60 gene. Regarding G. duodenalis, based on the SSU rRNA, bg, gdh, and tpi genes, the prevalence in domestic animals was 5.1% (31/608), with three assemblages identified: A (n = 1) in pigs, D (n = 1) in foxes, and E (n = 27) in geese, cattle, pigs, ducks, and sheep, along with mixed infection of A + E (n = 1) in one pig and B + E (n = 1) in one sheep. No G. duodenalis was detected in humans (0/116). CONCLUSIONS: The present results show that no overlap of subtypes between animals and villagers was found in Cryptosporidium spp. and G. duodenalis, indicating a minor role of domestic animals in infecting humans in this population. However, the presence of zoonotic protozoa in domestic animals highlights the need for special attention to high-risk individuals during close contact with domestic animals.

A novel two-way rebalancing strategy for identifying carbonylation sites.

BACKGROUND: As an irreversible post-translational modification, protein carbonylation is closely related to many diseases and aging. Protein carbonylation prediction for related patients is significant, which can help clinicians make appropriate therapeutic schemes. Because carbonylation sites can be used to indicate change or loss of protein function, integrating these protein carbonylation site data has been a promising method in prediction. Based on these protein carbonylation site data, some protein carbonylation prediction methods have been proposed. However, most data is highly class imbalanced, and the number of un-carbonylation sites greatly exceeds that of carbonylation sites. Unfortunately, existing methods have not addressed this issue adequately. RESULTS: In this work, we propose a novel two-way rebalancing strategy based on the attention technique and generative adversarial network (Carsite_AGan) for identifying protein carbonylation sites. Specifically, Carsite_AGan proposes a novel undersampling method based on attention technology that allows sites with high importance value to be selected from un-carbonylation sites. The attention technique can obtain the value of each sample's importance. In the meanwhile, Carsite_AGan designs a generative adversarial network-based oversampling method to generate high-feasibility carbonylation sites. The generative adversarial network can generate high-feasibility samples through its generator and discriminator. Finally, we use a classifier like a nonlinear support vector machine to identify protein carbonylation sites. CONCLUSIONS: Experimental results demonstrate that our approach significantly outperforms other resampling methods. Using our approach to resampling carbonylation data can significantly improve the effect of identifying protein carbonylation sites.

Moderate-to-vigorous intensity physical activity levels of children with intellectual disability during physical education classes.

Background: Physical education (PE) class is an excellent way to improve moderate-to-vigorous intensity physical activity (MVPA). Increasing number of research has explored the children's PA based on movement during PE classes, but data for children with intellectual disability (ID) is still lacking. Purpose: The purpose of this study was to investigate the current status of MVPA levels of children with ID during PE classes in China, as well as differences of MVPA levels according to gender and grade. Methods: Accelerometers were used to record MVPA levels of fifty-three children with severe ID from 9 to 16 years of age (mean age: 12.60 ± 1.66 years) during standard PE classes. Results: The mean time spent in MVPA during PE classes was 8.00 ± 2.10 min, meaning only 22.88% of PE class time was spent in MVPA. As grade levels progresses, time spent in MVPA during PE classes tended to decrease; the fourth-grade children tended to spend more time in MVPA during PE classes compared with the fifth-grade and the sixth-grade (9.15 vs. 7.61 vs. 7.25 min, all p < 0.05). Boys spend significantly more time in MVPA during PE classes than girls; both in the entire sample (9.20 vs. 5.70 min) as well as in each grade (9.76 vs. 6.09 min, 9.35 vs. 5.68 min, 8.31 vs. 5.59 min, all p < 0.05). Conclusion: Findings from this study indicate that the proportion of PE class spent in the MVPA of children with ID was lower than the 50% recommended by the U.S. Department of Health and Human Services (DHHS) and U.K. Association for Physical Education (AfPE). And the amount of MVPA participation varied by the grade and gender as well as by the activity performed. Therefore, in order to help children with ID achieve MVPA goals, educators need to reevaluate the PE curriculum as well as take due consideration of grade and gender when devising new content.

Experience of cardiopulmonary resuscitation by healthcare professionals in emergency departments: A descriptive phenomenological study.

BACKGROUND: Emergency department healthcare professionals have the most contact with patients in cardiac arrest, and their physical and mental state has a significant impact on the quality of cardiopulmonary resuscitation and patient outcomes. However, there is limited research discussing the experience of resuscitation by emergency department healthcare professionals. AIM: To explore the experiences of emergency department healthcare professionals in performing cardiopulmonary resuscitation. METHODS: A descriptive phenomenological study. The study used purposive sampling and selected 9 nurses and 6 physicians from the emergency departments of four general hospitals of different levels in western China between May 2022 and October 2022. Semi-structured interview guides and face-to-face interviews were used to collect information. Colaizzi analysis was used to analyze the data. RESULTS: The study identified 3 themes and 11 sub-themes. These themes and sub-themes include 1) emotional experience (A sense of achievement, A sense of powerlessness and trauma, Stress, Empathy, Psychological resilience strengthens), 2) cognitive growth (Understanding CPR rationally, Increasing concern for personal and family health, Mastering self-relaxation methods), and 3) the desire for continued development (Seeking professional development, Hoping for professional psychological assistance, Strengthening team support). CONCLUSIONS: The experience of performing cardiopulmonary resuscitation by healthcare professionals in emergency departments is dynamic, with changes in mood and cognitive growth. Managers in hospitals should pay attention to their experiences and need at different stages of career development and actively carry out targeted cognitive guidance, skills training, and psychological support to help them achieve professional development and physical and mental health. At the same time, to promote the development of CPR for all, it is recommended that the authorities actively improve the public infrastructure for first aid and related policy protection.

Cancer survival prediction by learning comprehensive deep feature representation for multiple types of genetic data.

BACKGROUND: Cancer is one of the leading death causes around the world. Accurate prediction of its survival time is significant, which can help clinicians make appropriate therapeutic schemes. Cancer data can be characterized by varied molecular features, clinical behaviors and morphological appearances. However, the cancer heterogeneity problem usually makes patient samples with different risks (i.e., short and long survival time) inseparable, thereby causing unsatisfactory prediction results. Clinical studies have shown that genetic data tends to contain more molecular biomarkers associated with cancer, and hence integrating multi-type genetic data may be a feasible way to deal with cancer heterogeneity. Although multi-type gene data have been used in the existing work, how to learn more effective features for cancer survival prediction has not been well studied. RESULTS: To this end, we propose a deep learning approach to reduce the negative impact of cancer heterogeneity and improve the cancer survival prediction effect. It represents each type of genetic data as the shared and specific features, which can capture the consensus and complementary information among all types of data. We collect mRNA expression, DNA methylation and microRNA expression data for four cancers to conduct experiments. CONCLUSIONS: Experimental results demonstrate that our approach substantially outperforms established integrative methods and is effective for cancer survival prediction. AVAILABILITY AND IMPLEMENTATION: https://github.com/githyr/ComprehensiveSurvival .

The frequency and subtype distribution of Blastocystis sp. in humans and domestic animals in households in Heilongjiang Province, China.

Blastocystis is an enteric protozoan able to infect humans and a large variety of animal hosts worldwide. It exhibits significant genetic diversity, with at least 17 subtypes (STs) identified to date, most of which have low host specificity. In the present study, a cross-sectional survey was conducted on Blastocystis infection among humans and domestic animals sharing habitats in northeastern China's Heilongjiang Province, in order to investigate the frequency and subtype distribution and to evaluate the risk of the zoonotic transmission of Blastocystis sp..Results show that the frequency was 10.5% (6/57), and three subtypes (ST1, ST2, and ST3) were found in humans; in animals, the frequency was 17.9% (46/257), and six subtypes (ST1, ST3, ST5, ST7, ST10, and ST26) were detected. A significant association between Blastocystis sp. infection and eating unwashed vegetables and fruits was found (P = 0.007). We found no effect on gender, age and season on Blastocystis sp. colonization. Phylogenetic analysis showed that Blastocystis ST7 sequences from chicken in two geographical locations formed two distinct clades. Alleles were identified using the Blastocystis 18S database, and a total of 10 different alleles were found in seven STs. Overlap of STs in humans and domestic animals (pig or cattle) was observed in Dongfanghong village. The findings of potentially zoonotic subtypes in domestic animals suggest that these animals may serve as reservoirs of human Blastocystis sp. infections. Multisectoral cooperation is needed to slow down the transmission of Blastocystis in domestic animals, minimize environmental contamination by Blastocystis cysts, and increase molecular epidemiological surveillance of Blastocystis sp. in humans and animals.

Using multisession tDCS stimulation as an early intervention on memory bias processing in subthreshold depression.

Transcranial direct current stimulation (tDCS) as an intervention tool has gained promising results in major depression disorder. However, studies related to subthreshold depression's (SD) cognitive deficits and neuromodulation approaches for the treatment of SD are still rare. We adopted Beck's cognitive model of depression and tested the tDCS stimulation effects on attentional and memory deficits on SD. First, this was a single-blinded, randomized, sham-controlled clinical trial to determine a 13-day tDCS modulation effect on 49 SD (27: Stimulation; 22: Sham) and 17 healthy controls. Second, the intervention effects of the consecutive and single-session tDCS were compared. Furthermore, the attentional and memory biases were explored in SD. Anodal tDCS was administrated over left dorsolateral prefrontal cortex for 13 consecutive days. Attentional and memory bias were assessed through a modified Sternberg task and a dot-probe task on the 1st, 2nd, and 15th day while their EEG was being recorded. After the 13-day tDCS stimulation (not after single-session stimulation), we found reduced memory bias (Stimulation vs. Sham, p = .02, r2  = .09) and decreased mid-frontal alpha power (p < .01, r2  = .13). In contrast, tDCS did not affect any attentional related behavioral or neural indexes (all ps > .15). Finally, reduced depressive symptoms (e.g., BDI score) were found for both groups. The criteria of SD varied across studies; the efficacy of this protocol should be tested in elderly patients. Our study suggests memory bias of SD can be modulated by the multisession tDCS and alpha power could serve as a neural index for intervention.

Joint learning sample similarity and correlation representation for cancer survival prediction.

BACKGROUND: As a highly aggressive disease, cancer has been becoming the leading death cause around the world. Accurate prediction of the survival expectancy for cancer patients is significant, which can help clinicians make appropriate therapeutic schemes. With the high-throughput sequencing technology becoming more and more cost-effective, integrating multi-type genome-wide data has been a promising method in cancer survival prediction. Based on these genomic data, some data-integration methods for cancer survival prediction have been proposed. However, existing methods fail to simultaneously utilize feature information and structure information of multi-type genome-wide data. RESULTS: We propose a Multi-type Data Joint Learning (MDJL) approach based on multi-type genome-wide data, which comprehensively exploits feature information and structure information. Specifically, MDJL exploits correlation representations between any two data types by cross-correlation calculation for learning discriminant features. Moreover, based on the learned multiple correlation representations, MDJL constructs sample similarity matrices for capturing global and local structures across different data types. With the learned discriminant representation matrix and fused similarity matrix, MDJL constructs graph convolutional network with Cox loss for survival prediction. CONCLUSIONS: Experimental results demonstrate that our approach substantially outperforms established integrative methods and is effective for cancer survival prediction.

Family factors associated with physical activity in children with intellectual disability: A systematic review.

This systematic review aimed to explore the influence of family factors on physical activity in children with intellectual disability. How and what family factors that specifically influence physical activity has not been compiled and reviewed previously. In accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, a systematic search was performed for articles published in English and Chinese without any year limits in six databases. Ten studies met the eligibility criteria and were included in the review. All studies were qualitatively integrated to identify and compare positive and negative family factors. A total of 1135 participants, of which 497 were children with intellectual disability while the other 638 participants were family members (parents, siblings and caregivers). The family factors of 6 themes and 18 sub-themes (10 positive, 7 negative and 1 inconclusive factors) were extracted. Overall, these results highlight the importance of encouragement, support and involvement by family members, concurrently it points out that parental psychological factors, socioeconomic status, responsibilities and electronic devices could both promote and hinder engagement in physical activity for children with intellectual disability. The findings accentuate the role of the family unit in helping determine the activity levels of children with intellectual disability. Future studies should include a wider range of participants and be longitudinal in nature, utilizing more accurate monitoring tools.

A novel C-terminal modification method enhanced the yield of human papillomavirus L1 or chimeric L1-L2 virus-like particles in the baculovirus system.

Human papillomavirus (HPV) major capsid protein L1 virus-like particles (VLPs) produced in the baculovirus system showed excellent safety and immunogenicity, but the relatively high production cost stands as a substantial barrier to extensive commercialization, especially in producing multivalent vaccines. Here, a novel method, C-terminal basic amino acid (aa) substitution, was developed for increasing VLP and chimeric VLP (cVLP) production in this system. A series of mutants of five HPV types, including three L1 VLPs (6L1, 11L1, and 52L1) and two L1-L2 cVLPs (16L1-33L2, 58L1-16L2), were constructed. We found that most mutants exhibited higher protein expression in Sf9 cells, among which the yields of the superior mutants, 6L1CS4, 11L1CS3, 52L1m4∆N13CS1, 16L1-33L2 CS1, and 58L1-16L2 CS3, were up to 40, 35, 20, 35, and 60 mg/L, which respectively increased by 4.2-, 7.3-, 5-, 2.5-, and 3.4-fold, and they also showed robust immunogenicity and great stabilities. Additionally, we found that the increased level of steady-state mRNA may play a crucial role in promoting L1 protein expression. Our results demonstrated that this novel method was cost-effective and can be used to reduce the production costs of L1 VLPs and L1-L2 cVLPs to develop broadly protective and affordable multivalent HPV vaccines.

Detection of preterm birth in electrohysterogram signals based on wavelet transform and stacked sparse autoencoder.

Based on electrohysterogram, this paper designed a new method using wavelet-based nonlinear features and stacked sparse autoencoder for preterm birth detection. For each sample, three level wavelet decomposition of a time series was performed. Approximation coefficients at level 3 and detail coefficients at levels 1, 2 and 3 were extracted. Sample entropy of the detail coefficients at levels 1, 2, 3 and approximation coefficients at level 3 were computed as features. The classifier was constructed based on stacked sparse autoencoder. In addition, stacked sparse autoencoder was further compared with extreme learning machine and support vector machine in relation to their classification performance of electrohysterogram. The experiment results reveal that classifier based on stacked sparse autoencoder showed better performance than the other two classifiers with an accuracy of 90%, a sensitivity of 92%, a specificity of 88%. The results indicate that the method proposed in this paper could be effective for detecting preterm birth in electrohysterogram and the framework designed in this work presents higher discriminability than other techniques.

Effect of sodium chloride on polyhydroxyalkanoate production from food waste fermentation leachate under different organic loading rate.

Polyhydroxyalkanoate (PHA) production integrated with anaerobic digestion is promising for food waste recycle. However, effect of salinity and high organic load in waste fermentation leachate (FWFL) on PHA production is unknown. Effects of sodium chloride (NaCl, 0, 5.0, 10.0 and 15.0 g/L) and organic loading rate (OLR, 1350 and 8433 mg COD/(L·d)) on the enrichment of PHA-accumulating microorganisms and PHA accumulation using FWFL were investigated in this research. Stable operation and obvious effect were observed under lower OLR with increasing NaCl concentration, but effect of NaCl was concealed by the inhibition caused by high OLR. Paracoccus was the dominant bacteria in all treatments with NaCl. Microbial community at low OLR and 5.0 g/L NaCl had the best performance reflected by kinetic parameters. Real FWFL with different NaCl concentrations was used in batch assays to verify the optimized enrichment strategy, reaching the maximum PHA content of 33.4% at 2.5 g/L NaCl.

Displaying 31RG-1 peptide on the surface of HPV16 L1 by use of a human papillomavirus chimeric virus-like particle induces cross-neutralizing antibody responses in mice.

Current available human papillomavirus (HPV) vaccines are based on the major capsid protein L1 virus-like particles (VLPs), which mainly induce type-specific neutralizing antibodies against vaccine types. Continuing to add more types of VLPs in a vaccine raises the complexity and cost of production which remains the principal impediment to achieve broad implementation of HPV vaccines, particularly in developing regions. In this study, we constructed 16L1-31L2 chimeric VLP (cVLP) by displaying HPV31 L2 aa.17-38 on the h4 coil surface region of HPV16 L1, and assessed its immunogenicity in mouse model. We found that the cVLP adjuvanted with alum plus monophosphoryl lipid A could induce cross-neutralizing antibody responses against 16 out of 17 tested HPV pseudoviruses, and the titer against HPV16 was as high as that was induced by HPV16 L1VLP (titer > 105), more importantly, titers over 103 were observed against two HR-HPVs including HPV31 (titer, 2,200) and -59 (titer, 1,013), among which HPV59 was not covered by Gardasil-9, and medium or low titers of cross-neutralizing antibodies against other 13 tested HPV pseudoviruses were also observed. Our data demonstrate that 16L1-31L2 cVLP is a promising candidate for the formulation of broader spectrum HPV vaccines.

Feature Extraction and Classification of EHG between Pregnancy and Labour Group Using Hilbert-Huang Transform and Extreme Learning Machine.

Preterm birth (PTB) is the leading cause of perinatal mortality and long-term morbidity, which results in significant health and economic problems. The early detection of PTB has great significance for its prevention. The electrohysterogram (EHG) related to uterine contraction is a noninvasive, real-time, and automatic novel technology which can be used to detect, diagnose, or predict PTB. This paper presents a method for feature extraction and classification of EHG between pregnancy and labour group, based on Hilbert-Huang transform (HHT) and extreme learning machine (ELM). For each sample, each channel was decomposed into a set of intrinsic mode functions (IMFs) using empirical mode decomposition (EMD). Then, the Hilbert transform was applied to IMF to obtain analytic function. The maximum amplitude of analytic function was extracted as feature. The identification model was constructed based on ELM. Experimental results reveal that the best classification performance of the proposed method can reach an accuracy of 88.00%, a sensitivity of 91.30%, and a specificity of 85.19%. The area under receiver operating characteristic (ROC) curve is 0.88. Finally, experimental results indicate that the method developed in this work could be effective in the classification of EHG between pregnancy and labour group.

Modulatory effect of romantic love on value estimation and its neural mechanism.

Any decision that is based upon personal preferences utilizes subjective values; however, for objectively equivalent items, whether romantic love modulates subjective value as well as the neural mechanism of this process remains unknown. In this functional MRI study, 30 items with equivalent value were first selected and assigned into three groups, and participants were trained to associate each group of items with their lover, a familiar person, or an unfamiliar person. Thereafter, the participant rated the values of the items during functional MRI scanning, after which they performed a post-test of memory of the associations. Behavioral results demonstrated that, although the items were well remembered, the items that were associated with the lover were rated significantly higher than the other images. Furthermore, we found higher activation related to the items associated with the lover than for those associated with a familiar person or an unfamiliar person in the striatum and the medial prefrontal cortex (related to cognitive control process). Finally, a morphometric analysis demonstrated that gray matter thickness in the striatum was positively associated with gray matter thickness in the medial prefrontal cortex but negatively correlated with the activation that was elicited by the items that were associated with the lover in the same brain area. Our results suggest that the romantic love-related brain region (the striatum) may modulate subjective value through the striatal-prefrontal pathway, further suggesting a potential bottom-up (control impulsivity) process.