Stretchable Ultrasound Metalens for Biomedical Zoom Imaging and Bone Quality Assessment with Subwavelength Resolution.

Ultrasound imaging is extensively used in biomedical science and clinical practice. Imaging resolution and tunability of imaging plane are key performance indicators, but both remain challenging to be improved due to the longer wavelength compared with light and the lack of zoom lens for ultrasound. Here, the ultrasound zoom imaging based on a stretchable planar metalens that simultaneously achieves the subwavelength imaging resolution and dynamic control of the imaging plane is reported. The proposed zoom imaging ultrasonography enables precise bone fracture diagnosis and comprehensive osteoporosis assessment. Millimeter-scale microarchitectures of the cortical bones at different depths can be selectively imaged with a 0.6-wavelength resolution. The morphological features of bone fractures, including the shape, size and position, are accurately detected. Based on the extracted ultrasound information of cancellous bones with healthy matrix, osteopenia and osteoporosis, a multi-index osteoporosis evaluation method is developed. Furthermore, it provides additional biological information in aspects of bone elasticity and attenuation to access the comprehensive osteoporosis assessment. The soft metalens also features flexibility and biocompatibility for preferable applications on wearable devices. This work provides a strategy for the development of high-resolution ultrasound biomedical zoom imaging and comprehensive bone quality diagnosis system.

Fecal microbiota transplantation alleviates mild-moderate COVID-19 associated diarrhoea and depression symptoms: A prospective study of a randomized, double-blind clinical trial.

Currently, the emergence of the endemic Coronavirus disease (COVID-19) situation still poses a serious threat to public health. However, it remains elusive about the role of fecal microbiota transplantation in treating COVID-19. We performed a randomized, double-blind, placebo-controlled clinical trial enrolling a cohort of 40 COVID-19 patients with mild-moderate symptoms. Our results showed that fecal microbiota transplantation provided an amelioration in diarrhoea (p = 0.026) of digestive system and depression (p = 0.006) of neuropsychiatric-related symptom in COVID-19 patients, respectively. Meanwhile, we found that the number of patients with diarrhoea decreased from 19 to 0 on day 7 after fecal microbiota transplantation treatment, and it was statistically changed compared to the placebo group (p = 0.047). Of note, the serum concentration of aspartate aminotransferase-to-alanine aminotransferase ratio (AST/ALT, fecal microbiota transplantation, pre vs. post: 0.966 vs. 0.817), a biomarker for predicting long COVID-19, was significantly reduced by fecal microbiota transplantation. In all, our study supports that fecal microbiota transplantation could be a novel therapeutic strategy for COVID-19 patients with diarrhoea and depressive symptoms, which is potentially valuable in ameliorating long COVID-19 symptoms.

Peripheral 5-HT Mediates Gonadotropin-Inhibitory Hormone-Induced Feeding Behavior and Energy Metabolism Disorder in Chickens via the 5-HT2C Receptor.

INTRODUCTION: Since the discovery of gonadotropin-inhibitory hormone (GnIH), it has been found to play a critical role in reproduction in vertebrates. Recently, a regulatory role of GnIH in appetite and energy metabolism has emerged, although its precise physiological mechanisms remain unknown. METHODS: Thus, the present study evaluated the effects of a single or long-term intraperitoneal GnIH treatment on the food intake, weight, and glucolipid metabolism of chickens, as well as investigating the possible neuroendocrinology factors and mechanisms involved in GnIH-induced obesity and glucolipid metabolism disorder. RESULTS: Our results show that the intraperitoneal administration of GnIH to chickens resulted in a marked body mass increase, hyperlipidemia, hyperglycemia, and glucose intolerance. Subsequently, the results of metabolomics studies and the pharmacological inhibition of the 5-HT2C receptor revealed that blocking the 5-HT2C receptor reinforced the effects of GnIH on food intake, body weight, and blood glucose and lipid levels, resulting in even worse cases of GnIH-induced hyperglycemia, hyperlipidemia, and hepatic lipid deposition. This suggests that, via the 5-HT2C receptor, peripheral 5-HT may act as a negative feedback regulator to interplay with GnIH and jointly control energy balance homeostasis in chickens. DISCUSSION: Our present study provides evidence of cross-talk between GnIH and 5-HT in food intake and energy metabolism at the in vivo pharmacological level, and it proposes a molecular basis for these interactions, suggesting that functional interactions between GnIH and 5-HT may open new avenues for understanding the mechanism of the neuroendocrine network involved in appetite and energy metabolism, as well as providing a new therapeutic strategy to prevent obesity, diabetes, and metabolic disorders.

Circadian light/dark cycle reversal exacerbates the progression of chronic kidney disease in mice.

Circadian disruption such as shift work, jet lag, has gradually become a global health issue and is closely associated with various metabolic disorders. The influence and mechanism of circadian disruption on renal injury in chronic kidney disease (CKD) remains inadequately understood. Here, we evaluated the impact of environmental light disruption on the progression of chronic renal injury in CKD mice. By using two abnormal light exposure models to induce circadian disruption, we found that circadian disruption induced by weekly light/dark cycle reversal (LDDL) significantly exacerbated renal dysfunction, accelerated renal injury, and promoted renal fibrosis in mice with 5/6 nephrectomy and unilateral ureteral obstruction (UUO). Mechanistically, RNA-seq analysis revealed significant immune and metabolic disorder in the LDDL-conditioned CKD kidneys. Consistently, renal content of ATP was decreased and ROS production was increased in the kidney tissues of the LDDL-challenged CKD mice. Untargeted metabolomics revealed a significant buildup of lipids in the kidney affected by LDDL. Notably, the level of ß-NMN, a crucial intermediate in the NAD+ pathway, was found to be particularly reduced. Moreover, we demonstrated that both ß-NMN and melatonin administration could significantly rescue the light-disruption associated kidney dysfunction. In conclusion, environmental circadian disruption may exacerbate chronic kidney injury by facilitating inflammatory responses and disturbing metabolic homeostasis. ß-NMN and melatonin treatments may hold potential as promising approaches for preventing and treating light-disruption associated CKD.

Prostate-specific antigen, androgen, progesterone and oestrogen receptors in Benign prostatic hyperplasia: human tissues and animal model study.

BACKGROUND: Direct evidence for the relationship between a large prostate (≥80 ml) and androgen receptor/PSA signal remains lacking in benign prostatic hyperplasia (BPH). Our aim is to identify whether the cause of a large prostate is related to progesterone receptor (PGR) androgen receptor (AR), oestrogen receptor α, ß (ERα,ß) and prostate-specific antigen (PSA). MATERIALS AND METHODS: Surgical specimens of BPH in plasmakinetic resection of the prostate (PKRP) with three groups of different prostate-sizes with mean volumes of 25.97 ml, 63.80 ml, and 122.37 ml were collected for immunohistochemical analysis of the tissue microarray with PGR, AR, PSA and ERs. Rats were castrated and treated with testosterone replacement to explore androgen and PGR, AR and ERs expression levels in the prostate. Quantitative real-time reverse transcription polymerase chain reaction (Rt-PCR) for mRNA detection of above genes was conducted. RESULTS: Immunoblotting, Rt-PCR and immunohistochemistry assays showed that PGR, PSA, AR, ERα expression levels were positively correlated with prostate size and that ERß expression levels were negatively correlated with prostate volume. Animal experiments have shown that prostate volume is decreased in castrated rats with decreased PGR, AR, ERα and increased ERß expression levels. CONCLUSION: PGR, AR, ERs signals can be regarded as important factors for large-sized prostates in BPH patients (≥100 ml).

GroEL triggers NLRP3 inflammasome activation through the TLR/NF-κB p-p65 axis in human periodontal ligament stem cells.

The interaction between bacteria and the host plays a vital role in the initiation and progression of systemic diseases, including gastrointestinal and oral diseases, due to the secretion of various virulence factors from these pathogens. GroEL, a potent virulence factor secreted by multiple oral pathogenic bacteria, is implicated in the damage of gingival epithelium, periodontal ligament, alveolar bone and other peripheral tissues. However, the underlying biomechanism is still largely unknown. In the present study, we verify that GroEL can trigger the activation of NLRP3 inflammasome and its downstream effector molecules, IL-1ß and IL-18, in human periodontal ligament stem cells (hPDLSCs) and resultantly induce high activation of gelatinases (MMP-2 and MMP-9) to promote the degradation of extracellular matrix (ECM). GroEL-mediated activation of the NLRP3 inflammasome requires the participation of Toll-like receptors (TLR2 and TLR4). High upregulation of TLR2 and TLR4 induces the enhancement of NF-κB (p-p65) signaling and promotes its nuclear accumulation, thus activating the NLRP3 inflammasome. These results are verified in a rat model with direct injection of GroEL. Collectively, this study provides insight into the role of virulence factors in bacteria-induced host immune response and may also provide a new clue for the prevention of periodontitis.

Backscatter measurement of cancellous bone using the ultrasound transit time spectroscopy.

Recently, ultrasound transit time spectroscopy (UTTS) was proposed as a promising method for bone quantitative ultrasound measurement. Studies have showed that UTTS could estimate the bone volume fraction and other trabecular bone structure in ultrasonic through-transmission measurements. The goal of this study was to explore the feasibility of UTTS to be adapted in ultrasonic backscatter measurement and further evaluate the performance of backscattered ultrasound transit time spectrum (BS-UTTS) in the measurement of cancellous bone density and structure. First, taking ultrasonic attenuation into account, the concept of BS-UTTS was verified on ultrasonic backscatter signals simulated from a set of scatterers with different positions and intensities. Then, in vitro backscatter measurements were performed on 26 bovine cancellous bone specimens. After a logarithmic compression of the BS-UTTS, a linear fitting of the log-compressed BS-UTTS versus ultrasonic propagated distance was performed and the slope and intercept of the fitted line for BS-UTTS were determined. The associations between BS-UTTS parameters and cancellous bone features were analyzed using simple linear regression. The results showed that the BS-UTTS could make an accurate deconvolution of the backscatter signal and predict the position and intensity of the simulated scatterers eliminating phase interference, even the simulated backscatter signal was with a relatively low signal-to-noise ratio. With varied positions and intensities of the scatterers, the slope of the fitted line for the log-compressed BS-UTTS versus ultrasonic propagated distance (i.e., slope of BS-UTTS for short) yield a high agreement (r2 = 99.84%-99.96%) with ultrasonic attenuation in simulated backscatter signal. Compared with the high-density cancellous bone, the low-density specimen showed more abundant backscatter impulse response in the BS-UTTS. The slope of BS-UTTS yield a significant correlation with bone mineral density (r = 0.87; p < 0.001), BV/TV (r = 0.87; p < 0.001), and cancellous bone microstructures (r up to 0.87; p < 0.05). The intercept of BS-UTTS was also significantly correlated with bone densities (r = -0.87; p < 0.001) and trabecular structures (|r|=0.43-0.80; p < 0.05). However, the slope of the BS-UTTS underestimated attenuation when measurements were performed experimentally. In addition, a significant non-linear relationship was observed between the measured attenuation and the attenuation estimated by the slope of the BS-UTTS. This study demonstrated that the UTTS method could be adapted to ultrasonic backscatter measurement of cancellous bone. The derived slope and intercept of BS-UTTS could be used in the measurement of bone density and microstructure. The backscattered ultrasound transit time spectroscopy might have potential in the diagnosis of osteoporosis in the clinic.

Ultrasonic Imaging of Deeper Bone Defect Using Virtual Source Synthetic Aperture with Phased Shift Migration: A Phantom Study.

Ultrasound imaging for bone is a difficult task in the field of medical ultrasound. Compared with other phase array techniques, the synthetic aperture (SA) has a better lateral resolution but a limited imaging depth due to the limited ultrasonic energy emitted by the single emitter in each transmission. In contrast, the virtual source (VS) synthetic aperture allows a simultaneous multi-element emission and could provide a higher ultrasonic incident energy in each transmission. Therefore, the VS might achieve a high imaging quality at a deeper depth for bone imaging than the traditional SA. In this study, we proposed the virtual source phase shift migration (VS-PSM) method to achieve ultrasonic imaging of the deeper bone defect featured in the multilayer structure. The proposed VS-PSM method was validated using standard soft tissue phantom and printed bone phantom with artificial defects. The image quality was evaluated in terms of contrast-to-noise ratios (CNR) and amplitudes of scatters and defects at different imaging depths. The results showed that the VS-PSM method could achieve a high imaging quality of the soft tissues with a significant improvement in the scattering amplitude and without a significant sacrifice of the lateral and axial resolution. The PSM was superior to the DAS in suppressing the background noise in the images. Compared with the traditional SA-PSM, the VS-PSM method could image deeper bone defects at different ultrasonic frequencies, with an average improvement of 50% in CNR. In conclusion, this study demonstrated that the proposed VS-PSM method could image deeper bone defects and might help the diagnosis of bone disease using ultrasonic imaging.

Prediction of martensite start temperature of steel combined with expert experience and machine learning.

The martensite start temperature (MS) plays a pivotal role in formulating heat treatment regimes for steel. This paper, through the compilation of experimental data from literature and the incorporation of expert knowledge to construct features, employs machine learning algorithms to predict the MS of steel. The study highlights that the ETR algorithm attains optimal prediction accuracy, and the inclusion of atomic features enhances the model's performance. Feature selection is accomplished by evaluating linear and nonlinear relationships between data using the Pearson correlation coefficient (PCC), variance inflation factor (VIF), and maximum information coefficient (MIC). Subsequently, the performance of machine learning models on unknown data is compared to validate the model's generalization ability. The introduction of SHAP values for model interpretability analysis unveils the influencing mechanisms between features and the target variable. Finally, utilizing a specific steel type as an illustration, the paper underscores the practical value of the model.

This study innovatively integrates experimental data, expert knowledge, and ETR algorithm for accurate MS prediction in steel, enhancing model performance with systematic feature selection and interpretability analysis, demonstrating practical utility.

Flavonoid Profiles in the Pulp of Different Lemon Cultivars and Their Antioxidant Activity Based on UPLC-Q-TOF-MS.

Previous studies have indicated that there may be differences among the varieties of lemon flavonoids, but the details have not yet been made clear, which limits the comprehensive use of different cultivated lemon varieties. In this study, ultra-performance liquid chromatography-quadrupole-time-of-flight-mass spectrometry (UPLC-Q-TOF-MS) and ultraviolet-visible spectroscopy (UV-Vis) were used to investigate the types and contents of flavonoids in the flesh of the main cultivated variety (Eureka) and five common lemon varieties, as well as their in vitro antioxidant activity. A total of 21 compounds were identified, five of which were common compounds. Among them, Verna, Lisbon, and Bearss each have characteristic components that can serve as potential criteria for variety identification. Each of the six varieties of lemon has strong antioxidant activity. The antioxidant activity of different lemon varieties is related to flavonoids. Therefore, Eureka and the other five varieties of lemon are good natural antioxidants, and the cultivation and industrial production of lemons should consider the needs and selection of suitable varieties.

Characterization and application of in situ curcumin/ZNP hydrogels for periodontitis treatment.

BACKGROUND: Periodontitis is a chronic inflammatory disease that occurs in tooth-supporting tissues. Controlling inflammation and alleviating periodontal tissue destruction are key factors in periodontal therapy. This study aimed to develop an in situ curcumin/zinc oxide (Cur/ZNP) hydrogel and investigate its characteristics and effectiveness in the treatment of periodontitis. METHODS: Antibacterial activity and cytotoxicity assays were performed in vitro. To evaluate the effect of the in situ Cur/ZNP hydrogel on periodontitis in vivo, an experimental periodontitis model was established in Sprague‒Dawley rats via silk ligature and inoculation of the maxillary first molar with Porphyromonas gingivalis. After one month of in situ treatment with the hydrogel, we examined the transcriptional responses of the gingiva to the Cur/ZNP hydrogel treatment and detected the alveolar bone level as well as the expression of osteocalcin (OCN) and osteoprotegerin (OPG) in the periodontal tissues of the rats. RESULTS: Cur/ZNPs had synergistic inhibitory effects on P. gingivalis and good biocompatibility. RNA sequencing of the gingiva showed that immune effector process-related genes were significantly induced by experimental periodontitis. Carcinoembryonic antigen-related cell adhesion molecule 1 (Ceacam1), which is involved in the negative regulation of bone resorption, was differentially regulated by the Cur/ZNP hydrogel but not by the Cur hydrogel or ZNP hydrogel. The Cur/ZNP hydrogel also had a stronger protective effect on alveolar bone resorption than both the Cur hydrogel and the ZNP hydrogel. CONCLUSION: The Cur/ZNP hydrogel effectively inhibited periodontal pathogenic bacteria and alleviated alveolar bone destruction while exhibiting favorable biocompatibility.

A cascading learning method with SegFormer for radiographic measurement of periodontal bone loss.

OBJECTIVE: Marginal alveolar bone loss is one of the key features of periodontitis and can be observed via panoramic radiographs. This study aimed to establish a cascading learning method with deep learning (DL) for precise radiographic bone loss (RBL) measurements at specific tooth positions. MATERIALS AND METHODS: Through the design of two tasks for tooth position recognition and tooth semantic segmentation using the SegFormer model, specific tooth's crown, intrabony portion, and suprabony portion of the roots were obtained. The RBL was subsequently measured by length through these three areas using the principal component analysis (PCA) principal axis. RESULTS: The average intersection over union (IoU) for the tooth position recognition task was 0.8906, with an F1-score of 0.9338. The average IoU for the tooth semantic segmentation task was 0.8465, with an F1-score of 0.9138. When the two tasks were combined, the average IoU was 0.7889, with an F1-score of 0.8674. The correlation coefficient between the RBL prediction results based on the PCA principal axis and the clinicians' measurements exceeded 0.85. Compared to those of the other two methods, the average precision of the predicted RBL was 0.7722, the average sensitivity was 0.7416, and the average F1-score was 0.7444. CONCLUSIONS: The method for predicting RBL using DL and PCA produced promising results, offering rapid and reliable auxiliary information for future periodontal disease diagnosis. CLINICAL RELEVANCE: Precise RBL measurements are important for periodontal diagnosis. The proposed RBL-SF can measure RBL at specific tooth positions and assign the bone loss stage. The ability of the RBL-SF to measure RBL at specific tooth positions can guide clinicians to a certain extent in the accurate diagnosis of periodontitis.

Hydrogen-Bond-Network Breakdown Boosts Selective CO2 Photoreduction by Suppressing H2 Evolution.

Conventional strategies for highly efficient and selective CO2 photoreduction focus on the design of catalysts and cocatalysts. In this study, we discover that hydrogen bond network breakdown in reaction system can suppress H2 evolution, thereby improving CO2 photoreduction performance. Photosensitive poly(ionic liquid)s are designed as photocatalysts owing to their strong hydrogen bonding with solvents. The hydrogen bond strength is tuned by solvent composition, thereby effectively regulating H2 evolution (from 0 to 12.6 mmol g-1 h-1). No H2 is detected after hydrogen bond network breakdown with trichloromethane or tetrachloromethane as additives. CO production rate and selectivity increase to 35.4 mmol g-1 h-1 and 98.9 % with trichloromethane, compared with 0.6 mmol g-1 h-1 and 26.2 %, respectively, without trichloromethane. Raman spectroscopy and theoretical calculations confirm that trichloromethane broke the systemic hydrogen bond network and subsequently suppressed H2 evolution. This hydrogen bond network breakdown strategy may be extended to other catalytic reactions involving H2 evolution.

Therapy of traditional Chinese medicine in Candida spp. and Candida associated infections: A comprehensive review.

Candida spp. are commonly a group of opportunistic dimorphic fungi, frequently causing diverse fungal infections in immunocompromised or immunosuppressant patients from mucosal disturbs (oropharyngeal candidiasis and vulvovaginal candidiasis) to disseminated infections (systemic candidiasis) with high morbidity and mortality. Importantly, several Candida species can be isolated from diseased individuals with digestive, neuropathic, respiratory, metabolic and autoimmune diseases. Due to increased resistance to conventional antifungal agents, the arsenal for antifungal purpose is in urgent need. Traditional Chinese Medicines (TCMs) are a huge treasury that can be used as promising candidates for antimycotic applications. In this review, we make a short survey of microbiological (morphology and virulence) and pathological (candidiasis and Candida related infections) features of and host immune response (innate and adaptive immunity) to Candida spp.. Based on the chemical structures and well-studied antifungal mechanisms, the monomers, extracts, decoctions, essential oils and other preparations of TCMs that are reported to have fair antifungal activities or immunomodulatory effects for anticandidal purpose are comprehensively reviewed. We also emphasize the importance of combination and drug pair of TCMs as useful anticandidal strategies, as well as network pharmacology and molecular docking as beneficial complements to current experimental approaches. This review construct a therapeutic module that can be helpful to guide in-future experimental and preclinical studies in the combat against fungal threats aroused by C. albicans and non-albicans Candida species.

Changes in Rhizosphere Soil Microorganisms and Metabolites during the Cultivation of Fritillaria cirrhosa.

Fritillaria cirrhosa is an important cash crop, and its industrial development is being hampered by continuous cropping obstacles, but the composition and changes of rhizosphere soil microorganisms and metabolites in the cultivation process of Fritillaria cirrhosa have not been revealed. We used metagenomics sequencing to analyze the changes of the microbiome in rhizosphere soil during a three-year cultivation process, and combined it with LC-MS/MS to detect the changes of metabolites. Results indicate that during the cultivation of Fritillaria cirrhosa, the composition and structure of the rhizosphere soil microbial community changed significantly, especially regarding the relative abundance of some beneficial bacteria. The abundance of Bradyrhizobium decreased from 7.04% in the first year to about 5% in the second and third years; the relative abundance of Pseudomonas also decreased from 6.20% in the first year to 2.22% in the third year; and the relative abundance of Lysobacter decreased significantly from more than 4% in the first two years of cultivation to 1.01% in the third year of cultivation. However, the relative abundance of some harmful fungi has significantly increased, such as Botrytis, which increased significantly from less than 3% in the first two years to 7.93% in the third year, and Talaromyces fungi, which were almost non-existent in the first two years of cultivation, significantly increased to 3.43% in the third year of cultivation. The composition and structure of Fritillaria cirrhosa rhizosphere metabolites also changed significantly, the most important of which were carbohydrates represented by sucrose (48.00-9.36-10.07%) and some amino acid compounds related to continuous cropping obstacles. Co-occurrence analysis showed that there was a significant correlation between differential microorganisms and differential metabolites, but Procrustes analysis showed that the relationship between bacteria and metabolites was closer than that between fungi and metabolites. In general, in the process of Fritillaria cirrhosa cultivation, the beneficial bacteria in the rhizosphere decreased, the harmful bacteria increased, and the relative abundance of carbohydrate and amino acid compounds related to continuous cropping obstacles changed significantly. There is a significant correlation between microorganisms and metabolites, and the shaping of the Fritillaria cirrhosa rhizosphere's microecology by bacteria is more relevant.

Automated extraction of Tridacna shell growth patterns via machine learning for enhanced paleoclimate/paleoweather research.

Tridacna spp. are valuable archives for paleoclimate and paleoweather research due to their distinct daily growth patterns and the sensitivity of the daily growth patterns to environment changes. However, manually identifying daily growth lines and measuring the daily growth increment width (DGIW) of Tridacna shells from Laser Scanning Confocal Microscopy (LSCM) images is a tedious task that has become a significant barrier to Tridacna studies. This paper addresses this challenge by integrating machine learning into Tridacna research for the first time to automate the calculation of the number of daily growth lines and DGIW of Tridacna shells. Specifically, we propose an unsupervised generative adversarial attention network called TriGAN to automatically recognize distinct daily growth lines of Tridacna shells from LSCM images. Utilizing modern Tridacna specimens collected from the South China Sea, our experimental results demonstrate that TriGAN can effectively reconstruct the ambiguous and blurred regions in LSCM images and produce higher quality images of daily growth patterns compared to existing image generation networks. Furthermore, the daily growth line number and DGIW of Tridacna shells can be counted automatically from the images recognized by TriGAN, which are in good agreement with the statistical results obtained manually from the original LSCM images (R = 0.7, p < 0.01 for the DGIW profile of T. gigas specimen MD1 and R = 0.6, p < 0.01 for T. derasa specimen XB10). This automated method provides an efficient solution for researching the laminar chronology of Tridacna.

Can artemisinin and its derivatives treat malaria in a host-directed manner?

Malaria is caused by an apicomplexan protozoan parasite, Plasmodium, and is transmitted through vectors. It remains a substantial health burden, especially in developing countries, leading to significant socioeconomic losses. Although the World Health Organization (WHO) has approved various antimalarial medications in the past two decades, the increasing resistance to these medications has worsened the situation. The development of drug resistance stems from genetic diversity among Plasmodium strains, impeding eradication efforts. Consequently, exploring innovative technologies and strategies for developing effective medications based on the host is crucial. Artemisinin and its derivatives (artemisinins) have been recommended by the WHO for treating malaria owing to their known effectiveness in killing the parasite. However, their potential to target the host for malaria treatment has not been investigated. This article concisely reviews the application of host-directed therapeutics, potential drug candidates targeting the host for treating malaria, and usage of artemisinins in numerous diseases. It underscores the importance of host-directed interventions for individuals susceptible to malaria, suggests the potential utility of artemisinins in host-directed malaria treatments, and posits that the modulation of host proteins with artemisinins may offer a means of intervening in host-parasite interactions. Further studies focusing on the host-targeting perspective of artemisinins can provide new insights into the mechanisms of artemisinin resistance and offer a unique opportunity for new antimalarial drug discovery.

Sodium Houttuyfonate Ameliorates DSS-induced Colitis Aggravated by Candida albicans through Dectin-1/NF-κB/miR-32-5p/NFKBIZ Axis Based on Intestinal microRNA Profiling.

Our previous research indicated that Sodium houttuyfonate (SH) can effectively ameliorate dextran sulfate sodium (DSS)-induced colitis exacerbated by Candida albicans. However, the underlying protective mechanism of SH remains unclear. Therefore, in this study, a mice colitis model was infected with C. albicans, and the total colonic miRNAs were assessed. Furthermore, the differentially expressed miRNAs were enriched, clustered, and analyzed. Moreover, based on the dual luciferase analysis of NFKBIZ modulation by miR-32-5p, the in vitro and in vivo therapeutic effects of SH on inflammatory response, fungal burden, oxidative stress, and apoptosis were assessed at transcriptional and translational levels in the presence of agonist and antagonist. A total of 1157 miRNAs were identified, 84 of which were differentially expressed. Furthermore, qRT-PCR validated that SH treatment improved 17 differentially expressed miRNAs with > fourfold upregulation or > sixfold downregulation. Similar to most differentially altered miRNA, C. albicans significantly increased Dectin-1, NF-κB, TNF-α, IL-1ß, IL-17A, and decreased miR-32-5p which negatively targeted NFKBIZ. In addition, SH treatment reduced inflammatory response and fungal burden in a colitis model with C. albicans infection. Further analyses indicated that in C. albicans infected Caco2 cells, SH inhibited fungal growth, oxidative stress, and apoptosis by increasing Dectin-1, NF-κB, NFKBIZ, TNF-α, IL-1ß, IL-17A, and decreasing miR-32-5p. Therefore, SH can ameliorate the severity of colitis aggravated by C. albicans via the Dectin-1/NF-κB/miR-32-5p/NFKBIZ axis.

Hepatic steatosis predicts metachronous liver metastasis in colorectal cancer patients: a nested case-control study and systematic review.

Nearly twenty-five percent of colorectal cancer (CRC) patients develop metachronous colorectal liver metastasis (CRLM) after curative surgery. Hepatosteatosis is the most prevalent liver condition worldwide, but its impact on the incidence of metachronous CRLM is understudied. In the present study, we aimed to investigate the predictive value of hepatic steatosis on the development of metachronous CRLM. First, a nested case-control study was conducted, enrolling stage I to III CRC patients in the National Colorectal Cancer Cohort (NCRCC) database. Metachronous CRLM patients and recurrence-free patients were matched via propensity-score matching. Fatty liver was identified based on treatment-naïve CT scans and the degree of hepatic fibrosis was scored. Multivariable analysis was conducted to investigate the association between fatty liver and metachronous CRLM. In our database, a total of 414 patients were included. Metachronous CRLM patients had considerably higher rates of hepatic steatosis (30.9% versus 15.9%, P<0.001) and highly fibrotic liver (11.6% versus 2.9%, P=0.001) compared to recurrence-free patients. Multivariable analysis showed that fatty liver (odds ratios [OR]=1.99, 95% confidence interval [CI] 1.19-3.30, P=0.008) and fibrotic liver (OR=4.27, 95% CI 1.54-11.81, P=0.005) were associated with high risk of metachronous CRLM. Further, a systematic literature review was performed to assess available evidence on the association between hepatosteatosis and development of metachronous CRLM. In the systematic review, 1815 patients were pooled from eligible studies, and hepatic steatosis remained a significant risk factor for metachronous CRLM (OR=1.90, 95% CI 1.35-2.66, P<0.001, I2=25.3%). In conclusion, our data suggest that patients with a steatotic liver and a high fibrosis score at CRC diagnosis have elevated risk of developing metachronous CRLM.

Super-resolution reconstruction of ultrasound image using a modified diffusion model.

Objective. This study aims to perform super-resolution (SR) reconstruction of ultrasound images using a modified diffusion model, designated as the diffusion model for ultrasound image super-resolution (DMUISR). SR involves converting low-resolution images to high-resolution ones, and the proposed model is designed to enhance the suitability of diffusion models for this task in the context of ultrasound imaging.Approach. DMUISR incorporates a multi-layer self-attention (MLSA) mechanism and a wavelet-transform based low-resolution image (WTLR) encoder to enhance its suitability for ultrasound image SR tasks. The model takes interpolated and magnified images as input and outputs high-quality, detailed SR images. The study utilized 1,334 ultrasound images from the public fetal head-circumference dataset (HC18) for evaluation.Main results. Experiments were conducted at 2× , 4× , and 8×  magnification factors. DMUISR outperformed mainstream ultrasound SR methods (Bicubic, VDSR, DECUSR, DRCN, REDNet, SRGAN) across all scales, providing high-quality images with clear structures and rich detailed textures in both hard and soft tissue regions. DMUISR successfully accomplished multiscale SR reconstruction while suppressing over-smoothing and mode collapse problems. Quantitative results showed that DMUISR achieved the best performance in terms of learned perceptual image patch similarity, with a significant decrease of over 50% at all three magnification factors (2× , 4× , and 8× ), as well as improvements in peak signal-to-noise ratio and structural similarity index measure. Ablation experiments validated the effectiveness of the MLSA mechanism and WTLR encoder in improving DMUISR's SR performance. Furthermore, by reducing the number of diffusion steps, the computational time of DMUISR was shortened to nearly one-tenth of its original while maintaining image quality without significant degradation.Significance. This study demonstrates that the modified diffusion model, DMUISR, provides superior performance for SR reconstruction of ultrasound images and has potential in improving imaging quality in the medical ultrasound field.