PATTERNFINDER: combined analysis of DNA regulatory sequences and double-helix stability

BACKGROUND: Regulatory regions that function in DNA replication and gene transcription contain specific sequences that bind proteins as well as less-specific sequences in which the double helix is often easy to unwind. Progress towards predicting and characterizing regulatory regions could be accelerated by computer programs that perform a combined analysis of specific sequences and DNA unwinding properties. RESULTS: Here we present PATTERNFINDER, a web server that searches DNA sequences for matches to specific or flexible patterns, and analyzes DNA helical stability. A batch mode of the program generates a tabular map of matches to multiple, different patterns. Regions flanking pattern matches can be targeted for helical stability analysis to identify sequences with a minimum free energy for DNA unwinding. As an example application, we analyzed a regulatory region of the human c-myc proto-oncogene consisting of a single-strand-specific protein binding site within a DNA region that unwindsin vivo. The predicted region of minimal helical stability overlapped both the protein binding site and the unwound DNA region identified experimentally. CONCLUSIONS: The PATTERNFINDER web server permits localization of known functional elements or landmarks in DNA sequences as well as prediction of potential new elements. Batch analysis of multiple patterns facilitates the annotation of DNA regulatory regions. Identifying specific pattern matches linked to DNA with low helical stability is useful in characterizing regulatory regions for transcription, replication and other processes and may predict functional DNA unwinding elements. PATTERNFINDER can be accessed freely at

Global Control of Tuberculosis: Current Status and Future Prospects

Tuberculosis is a zoonotic disease that is caused by mycobacterium tuberculosis complex and can infect humans, livestock, and wildlife. It spreads primarily through the respiratory tract and was the leading cause of death due to a single infectious disease before the COVID-19 pandemic. TB is a global public health emergency that has reemerged over the past few decades. Substantial efforts are needed to achieve the goals of the End TB Strategy. The World Health Organization has estimated that approximately 9.9 million people worldwide contracted TB in 2020 and that approximately 140,000 of the 10 million new cases of active TB in 2019 were zoonotic TB. During the COVID-19 pandemic, the number of new TB diagnoses and reports decreased sharply, from 7.1 million in 2019 to 5.8 million in 2020, returning to 2012 levels far below the approximately 10 million TB cases in 2020. Simultaneously, the global decrease in the absolute number of TB deaths until 2019 was followed by an increase in 2020 in four of the six WHO regions and most of the 30 high-TB-burden countries. Therefore, extensive immediate actions worldwide are required to restore the health system, and innovations are needed to accelerate progress toward a tuberculosis-free world

Effect of mycotoxins contaminated corn on growth nutrient digestibility and in vitro rumen fermentation in goats

Two trials (in vivo and in vitro) were conducted to evaluate corn naturally contaminated with mycotoxins, majority being aflatoxin B1 (AFB1) on the performance, nutrient digestion and rumen fermentation in growing goats. China Lezhi black goats (12), weighing 16.39 to 16.45 kg, were fed with the diet of 40% concentrate (the mycotoxin naturally contaminated diet containing 74.49 μg/kg AFB1, 2.08 μg/kg AFB2, 59.71 μg/kg DON and 36.51 μg/kg ZEN) for 28 days. The results showed that the contaminated corn had no significant effect on feed intake but decreased the average daily gain (ADG) and feed conversion ratio (FCR) in growing goats. Digestibility of crude protein (CP) in the trial group was significantly lower than the control group and the digestibilities of acid detergent fibre (ADF) and neutral detergent fibre (NDF) decreased too, but not significantly. Neither volatile fatty acid (VFA) nor pH was significantly different between the 2 groups. The ammonia nitrogen (NH3-N) in the trial group was lower in both in vivo trial and in vitro trial (0 h to 3 h). In in vitro experiment, ruminal fluids were collected from 4 China Lezhi goats and incubated at 39°C for 48 h with control corn or AFB1 contaminated corn. The total gas production and gas production rate in the trial group were significantly lower than the control group. These reductions showed the negative effects of the naturally contaminated AFB1 corn on nutrient digestibility and rumen function in growing goats

Semi-supervised Optimal Transport with Self-paced Ensemble for Cross-hospital Sepsis Early Detection

The utilization of computer technology to solve problems in medical scenarios has attracted considerable attention in recent years, which still has great potential and space for exploration. Among them, machine learning has been widely used in the prediction, diagnosis and even treatment of Sepsis. However, state-of-the-art methods require large amounts of labeled medical data for supervised learning. In real-world applications, the lack of labeled data will cause enormous obstacles if one hospital wants to deploy a new Sepsis detection system. Different from the supervised learning setting, we need to use known information (e.g., from another hospital with rich labeled data) to help build a model with acceptable performance, i.e., transfer learning. In this paper, we propose a semi-supervised optimal transport with self-paced ensemble framework for Sepsis early detection, called SPSSOT, to transfer knowledge from the other that has rich labeled data. In SPSSOT, we first extract the same clinical indicators from the source domain (e.g., hospital with rich labeled data) and the target domain (e.g., hospital with little labeled data), then we combine the semi-supervised domain adaptation based on optimal transport theory with self-paced under-sampling to avoid a negative transfer possibly caused by covariate shift and class imbalance. On the whole, SPSSOT is an end-to-end transfer learning method for Sepsis early detection which can automatically select suitable samples from two domains respectively according to the number of iterations and align feature space of two domains. Extensive experiments on two open clinical datasets demonstrate that comparing with other methods, our proposed SPSSOT, can significantly improve the AUC values with only 1% labeled data in the target domain in two transfer learning scenarios, MIMIC $rightarrow$ Challenge and Challenge $rightarrow$ MIMIC.Comment: 14 pages, 9 figure

Prostate-targeted biodegradable nanoparticles loaded with androgen receptor silencing constructs eradicate xenograft tumors in mice

BACKGROUND: Prostate cancer is the major cause of cancer death in men and the androgen receptor (AR) has been shown to play a critical role in the progression of the disease. Our previous reports showed that knocking down the expression of the AR gene using a siRNA-based approach in prostate cancer cells led to apoptotic cell death and xenograft tumor eradication. In this study, we utilized a biodegradable nanoparticle to deliver the therapeutic AR shRNA construct specifically to prostate cancer cells. MATERIALS & METHODS: The biodegradable nanoparticles were fabricated using a poly(dl-lactic-co-glycolic acid) polymer and the AR shRNA constructs were loaded inside the particles. The surface of the nanoparticles were then conjugated with prostate-specific membrane antigen aptamer A10 for prostate cancer cell-specific targeting. RESULTS: A10-conjugation largely enhanced cellular uptake of nanoparticles in both cell culture- and xenograft-based models. The efficacy of AR shRNA encapsulated in nanoparticles on AR gene silencing was confirmed in PC-3/AR-derived xenografts in nude mice. The therapeutic property of A10-conjugated AR shRNA-loaded nanoparticles was evaluated in xenograft models with different prostate cancer cell lines: 22RV1, LAPC-4 and LNCaP. Upon two injections of the AR shRNA-loaded nanoparticles, rapid tumor regression was observed over 2 weeks. Consistent with previous reports, A10 aptamer conjugation significantly enhanced xenograft tumor regression compared with nonconjugated nanoparticles. DISCUSSION: These data demonstrated that tissue-specific delivery of AR shRNA using a biodegradable nanoparticle approach represents a novel therapy for life-threatening prostate cancers

Coupling effects of Fe(II) and CaCO3 application on cadmium uptake and accumulation in rice (Oryza sativa L.)

Excessive cadmium (Cd) in rice, caused by Cd pollution of farmlands, poses a serious threat to human health. In this study, a pot experiment was conducted to investigate the effects of two doses of CaCO3 (Ca1: 2 g kg-1, Ca2: 10g kg-1), two types of Fe(II) (EDTA-Fe(II) and FeSO4; 0.14 g Fe kg-1), and their combined application on the uptake and accumulation of Cd in rice plants grown in Cd-contaminated acidic soil. The results revealed that FeSO4 significantly increased rice grain biomass, whereas the other treatments had no significant effects. Further, the addition of EDTA-Fe(II) or FeSO4 significantly enhanced iron plaque formation on the root surface and increased the Fe content in the rice plants and porewater. Compared to the control, CaCO3 addition weakened the formation of iron plaque and reduced the Fe concentration in the porewater and root tissue, stems and leaves, whereas the Fe concentration in brown rice and the husks remained unaffected. Combined application of CaCO3 and Fe(II) significantly promoted the formation of iron plaque and increased the Fe concentration in brown rice. However, the Cd concentration in the iron plaque was reduced by CaCO3 addition but increased by Fe(II) treatment. Notably, all treatments reduced the Cd concentration in all rice plant tissues. The application of Ca1, Ca2, EDTA-Fe(II), FeSO4, Ca1+EDTA-Fe(II), Ca1+FeSO4, Ca2+EDTA-Fe(II) and Ca2+FeSO4 significantly reduced the Cd concentration in brown rice by 69%, 63%, 51%, 60%, 46%, 39%, 38%, and 29%, respectively. These results indicate that the application of CaCO3, EDTA-Fe(II)/FeSO4, or their combination can effectively reduce Cd accumulation and translocation in rice plants

OnUVS: Online Feature Decoupling Framework for High-Fidelity Ultrasound Video Synthesis

Ultrasound (US) imaging is indispensable in clinical practice. To diagnose certain diseases, sonographers must observe corresponding dynamic anatomic structures to gather comprehensive information. However, the limited availability of specific US video cases causes teaching difficulties in identifying corresponding diseases, which potentially impacts the detection rate of such cases. The synthesis of US videos may represent a promising solution to this issue. Nevertheless, it is challenging to accurately animate the intricate motion of dynamic anatomic structures while preserving image fidelity. To address this, we present a novel online feature-decoupling framework called OnUVS for high-fidelity US video synthesis. Our highlights can be summarized by four aspects. First, we introduced anatomic information into keypoint learning through a weakly-supervised training strategy, resulting in improved preservation of anatomical integrity and motion while minimizing the labeling burden. Second, to better preserve the integrity and textural information of US images, we implemented a dual-decoder that decouples the content and textural features in the generator. Third, we adopted a multiple-feature discriminator to extract a comprehensive range of visual cues, thereby enhancing the sharpness and fine details of the generated videos. Fourth, we constrained the motion trajectories of keypoints during online learning to enhance the fluidity of generated videos. Our validation and user studies on in-house echocardiographic and pelvic floor US videos showed that OnUVS synthesizes US videos with high fidelity.Comment: 14 pages, 13 figures and 6 table