Optimization of fermentation conditions and quality evaluation of Chaenomeles sinensis glutinous rice wine

The present study was conducted to optimize fermentation conditions for preparation of Chaenomeles sinensis Glutinous Rice Wine (CRW). The dynamic changes of main substances in the liquor during fermentation process, aroma components, biologically active substances and antioxidant capacity in the CRW after 6 months of aging were tested. The results showed that under optimized conditions, the yield and alcohol content of wine was 44.97 and 20.00%, respectively. After aging, 64 aroma components were detected in the wine, mainly alcohols and esters. The alcohol content of the CRW was 14.8%. Polyphenols and flavonoids reached 0.23 g/L and 0.037 g/L respectively. Furthermore, the CRW had an excellent free radical scavenging ability.

Supplementary Information

The online version contains supplementary material available at 10.1007/s13197-024-05934-0.

A multimodal framework based on deep belief network for human locomotion intent prediction

Accurate prediction of human locomotion intent benefits the seamless switching of lower limb exoskeleton controllers in different terrains to assist humans in walking safely. In this paper, a deep belief network (DBN) was developed to construct a multimodal framework for recognizing various locomotion modes and predicting transition tasks. Three fusion strategies (data level, feature level, and decision level) were explored, and optimal network performance was obtained. This method could be tested on public datasets. For the continuous performance of steady state, the best prediction accuracy achieved was 97.64% in user-dependent testing and 96.80% in user-independent testing. During the transition state, the system accurately predicted all transitions (user-dependent: 96.37%, user-independent: 95.01%). The multimodal framework based on DBN can accurately predict the human locomotion intent. The experimental results demonstrate the potential of the proposed model in the volition control of the lower limb exoskeleton.

Ultra-low frequency magnetic energy focusing for highly effective wireless powering of deep-tissue implantable electronic devices

The limited lifespan of batteries is a challenge in the application of implantable electronic devices. Existing wireless power technologies such as ultrasound, near-infrared light and magnetic fields cannot charge devices implanted in deep tissues, resulting in energy attenuation through tissues and thermal generation. Herein, an ultra-low frequency magnetic energy focusing (ULFMEF) methodology was developed for the highly effective wireless powering of deep-tissue implantable devices. A portable transmitter was used to output the low-frequency magnetic field (<50 Hz), which remotely drives the synchronous rotation of a magnetic core integrated within the pellet-like implantable device, generating an internal rotating magnetic field to induce wireless electricity on the coupled coils of the device. The ULFMEF can achieve energy transfer across thick tissues (up to 20 cm) with excellent transferred power (4-15 mW) and non-heat effects in tissues, which is remarkably superior to existing wireless powering technologies. The ULFMEF is demonstrated to wirelessly power implantable micro-LED devices for optogenetic neuromodulation, and wirelessly charged an implantable battery for programmable electrical stimulation on the sciatic nerve. It also bypassed thick and tough protective shells to power the implanted devices. The ULFMEF thus offers a highly advanced methodology for the generation of wireless powered biodevices.

Impact of perioperative low-molecular-weight heparin therapy on clinical events of elderly patients with prior coronary stents implanted > 12 months undergoing non-cardiac surgery: a randomized, placebo-controlled trial

BACKGROUND

Little is known about the safety and efficacy of discontinuing antiplatelet therapy via LMWH bridging therapy in elderly patients with coronary stents implanted for > 12 months undergoing non-cardiac surgery. This randomized trial was designed to compare the clinical benefits and risks of antiplatelet drug discontinuation via LMWH bridging therapy.

METHODS

Patients were randomized 1:1 to receive subcutaneous injections of either dalteparin sodium or placebo. The primary efficacy endpoint was cardiac or cerebrovascular events. The primary safety endpoint was major bleeding.

RESULTS

Among 2476 randomized patients, the variables (sex, age, body mass index, comorbidities, medications, and procedural characteristics) and percutaneous coronary intervention information were not significantly different between the bridging and non-bridging groups. During the follow-up period, the rate of the combined endpoint in the bridging group was significantly lower than in the non-bridging group (5.79% vs. 8.42%, p = 0.012). The incidence of myocardial injury in the bridging group was significantly lower than in the non-bridging group (3.14% vs. 5.19%, p = 0.011). Deep vein thrombosis occurred more frequently in the non-bridging group (1.21% vs. 0.4%, p = 0.024), and there was a trend toward a higher rate of pulmonary embolism (0.32% vs. 0.08%, p = 0.177). There was no significant difference between the groups in the rates of acute myocardial infarction (0.81% vs. 1.38%), cardiac death (0.24% vs. 0.41%), stroke (0.16% vs. 0.24%), or major bleeding (1.22% vs. 1.45%). Multivariable analysis showed that LMWH bridging, creatinine clearance < 30 mL/min, preoperative hemoglobin < 10 g/dL, and diabetes mellitus were independent predictors of ischemic events. LMWH bridging and a preoperative platelet count of < 70 × 109/L were independent predictors of minor bleeding events.

CONCLUSIONS

This study showed the safety and efficacy of perioperative LMWH bridging therapy in elderly patients with coronary stents implanted > 12 months undergoing non-cardiac surgery. An alternative approach might be the use of bridging therapy with half-dose LMWH.

TRIAL REGISTRATION

ISRCTN65203415.

Small GTPase Rab7 is involved in stress adaptation to carbon starvation to ensure the induced cellulase biosynthesis in Trichoderma reesei

BACKGROUND

The saprophytic filamentous fungus Trichoderma reesei represents one of the most prolific cellulase producers. The bulk production of lignocellulolytic enzymes by T. reesei not only relies on the efficient transcription of cellulase genes but also their efficient secretion after being translated. However, little attention has been paid to the functional roles of the involved secretory pathway in the high-level production of cellulases in T. reesei. Rab GTPases are key regulators in coordinating various vesicle trafficking associated with the eukaryotic secretory pathway. Specifically, Rab7 is a representative GTPase regulating the transition of the early endosome to the late endosome followed by its fusion to the vacuole as well as homotypic vacuole fusion. Although crosstalk between the endosomal/vacuolar pathway and the secretion pathway has been reported, the functional role of Rab7 in cellulase production in T. reesei remains unknown.

RESULTS

A TrRab7 was identified and characterized in T. reesei. TrRab7 was shown to play important roles in T. reesei vegetative growth and vacuole morphology. Whereas knock-down of Trrab7 significantly compromised the induced production of T. reesei cellulases, overexpression of the key transcriptional activator, Xyr1, restored the production of cellulases in the Trrab7 knock-down strain (Ptcu-rab7KD) on glucose, indicating that the observed defective cellulase biosynthesis results from the compromised cellulase gene transcription. Down-regulation of Trrab7 was also found to make T. reesei more sensitive to various stresses including carbon starvation. Interestingly, overexpression of Snf1, a serine/threonine protein kinase known as an energetic sensor, partially restored the cellulase production of Ptcu-rab7KD on Avicel, implicating that TrRab7 is involved in an energetic adaptation to carbon starvation which contributes to the successful cellulase gene expression when T. reesei is transferred from glucose to cellulose.

CONCLUSIONS

TrRab7 was shown to play important roles in T. reesei development and a stress response to carbon starvation resulting from nutrient shift. This adaptation may allow T. reesei to successfully initiate the inducing process leading to efficient cellulase production. The present study provides useful insights into the functional involvement of the endosomal/vacuolar pathway in T. reesei development and hydrolytic enzyme production.

Remnant cholesterol trajectory and subclinical arteriosclerosis: a 10-year longitudinal study of Chinese adults

We aimed to identify different trajectories of remnant cholesterol (RC) and investigate the association of RC trajectories with vascular endothelial function and atherosclerosis progression in a longitudinal cohort of the Chinese population. A total of 521 participants were included in the flow-mediated vasodilation (FMD) subcohort study, and 7775 participants were included in the brachial-ankle pulse wave velocity (baPWV) subcohort study. All participants had ≥ 3 medical examinations during the 10-year follow-up period. In the FMD subcohort study, three distinct RC trajectories were identified according to the RC range and changing pattern over time: "low" (57.58%), "moderate" (30.90%) and "high" (11.52%). The proportion of the three groups with vascular endothelial dysfunction (FMD < 7.0%) was 20.00%, 39.75% and 60.00% respectively. Taking the low group as a reference, participants in the moderate and high groups had over 1.88 and 2.94 times the odds of vascular endothelial dysfunction (P = 0.048). In the baPWV subcohort study, three distinct RC trajectories were also identified: "low" (54.29%), "moderate" (38.97%) and "high" (6.74%). The proportion of the three groups with atherosclerosis (baPWV > 1400 cm/s) was 38.79%, 51.26% and 59.01% respectively. Taking the low group as a reference, participants in the moderate and high groups had over 1.46 and 2.16 times the odds of atherosclerosis (P < 0.001). The findings indicated that distinct RC trajectories are significantly associated with vascular endothelial function and atherosclerosis. Regular monitoring to identify persistent increases in RC may be more helpful in identifying individuals with a high risk of cardiovascular disease.

Effect of resistance circuit training on comprehensive health indicators in older adults: a systematic review and meta-analysis

The aging process leads to the degeneration of body structure and function. The objective of this study is to conduct a systematic review and meta-analysis of the effects of resistance circuit training (RCT) on comprehensive health indicators of older adults. PubMed, Embase, and Web of Science were searched until August 2023. Primary outcomes were body composition, muscle strength, cardiorespiratory endurance, blood pressure, and functional autonomy. Muscle function and exercise intensity subgroups were analyzed. RCT reduces body fat (MD = - 5.39 kg, 95% CI - 10.48 to - 0.29), BMI (MD = - 1.22, 95% CI - 2.17 to - 0.26), and body weight (MD = - 1.28 kg, 95% CI - 1.78 to - 0.78), and increases lean body mass (MD = 1.42 kg, 95% CI 0.83-2.01) in older adults. It improves upper limb strength (SMD = 2.09, 95% CI 1.7-2.48), lower limb strength (SMD = 2.03, 95% CI 1.56-2.51), cardiorespiratory endurance (MD = 94 m, 95% CI 25.69-162.67), and functional autonomy (MD = - 1.35, 95% CI - 1.73 to - 0.96). High-intensity RCT benefits BMI and body weight, while low-intensity exercise reduces blood pressure. RCT improves muscle function in push, pull, hip, and knee movements in older adults. RCT improves body composition, muscle strength, cardiorespiratory endurance, blood pressure, and functional autonomy in older adults. High-intensity training is superior for body composition, while moderate to low intensity training is more effective for lowering blood pressure.

MODELS: a six-step framework for developing an infectious disease model

Since the COVID-19 pandemic began, a plethora of modeling studies related to COVID-19 have been released. While some models stand out due to their innovative approaches, others are flawed in their methodology. To assist novices, frontline healthcare workers, and public health policymakers in navigating the complex landscape of these models, we introduced a structured framework named MODELS. This framework is designed to detail the essential steps and considerations for creating a dependable epidemic model, offering direction to researchers engaged in epidemic modeling endeavors.

EGFR of platelet regulates macrophage activation and bacterial phagocytosis function

BACKGROUND

Beyond their crucial role in hemostasis, platelets possess the ability to regulate inflammation and combat infections through various mechanisms. Stringent control of macrophage activation is essential during innate immune responses in sepsis. Macrophages are considered crucial phagocytic cells that aid in the elimination of pathogens. Platelet interactions with monocytes-macrophages are known to be significant in the response against bacterial infections, but the primary mediator driving these interactions remains unclear. EGFR plays critical role in the regulation of inflammation and infection through various mechanisms.

RESULTS

The overexpression of platelets by thrombopoietin (TPO) leads to the sequestration of both pro-inflammatory (IL-6/IL-1) and anti-inflammatory (IL-10) cytokines in the organ tissue of septic mice. Epidermal growth factor receptor (EGFR) is critical for platelet activation in sepsis. EGFR-licensed platelets enhance macrophage immune function, including the production of reactive oxygen species (ROS) and the clearance of bacteria. Platelet EGFR also induces M1 macrophage polarization by increasing the expression of inducible nitric oxide synthase (iNOS) and CD64.

CONCLUSION

EGFR can activate platelet immune function. Moreover, activated platelets efficiently regulate bacterial phagocytosis and pro-inflammatory function of macrophages through an EGFR-dependent pathway.

Focusing on mitochondria in the brain: from biology to therapeutics

Mitochondria have multiple functions such as supplying energy, regulating the redox status, and producing proteins encoded by an independent genome. They are closely related to the physiology and pathology of many organs and tissues, among which the brain is particularly prominent. The brain demands 20% of the resting metabolic rate and holds highly active mitochondrial activities. Considerable research shows that mitochondria are closely related to brain function, while mitochondrial defects induce or exacerbate pathology in the brain. In this review, we provide comprehensive research advances of mitochondrial biology involved in brain functions, as well as the mitochondria-dependent cellular events in brain physiology and pathology. Furthermore, various perspectives are explored to better identify the mitochondrial roles in neurological diseases and the neurophenotypes of mitochondrial diseases. Finally, mitochondrial therapies are discussed. Mitochondrial-targeting therapeutics are showing great potentials in the treatment of brain diseases.

Utility of paired plasma and drainage fluid mNGS in diagnosing acute intra-abdominal infections with sepsis

BACKGROUND

Metagenomic next-generation sequencing (mNGS) has been increasingly applied in sepsis. We aimed to evaluate the diagnostic and therapeutic utility of mNGS of paired plasma and peritoneal drainage (PD) fluid samples in comparison to culture-based microbiological tests (CMTs) among critically ill patients with suspected acute intra-abdominal infections (IAIs).

METHODS

We conducted a prospective study from October 2021 to December 2022 enrolling septic patients with suspected IAIs (n = 111). Pairwise CMTs and mNGS of plasma and PD fluid were sent for pathogen detection. The mNGS group underwent therapeutic regimen adjustment based on mNGS results for better treatment. The microbial community structure, clinical features, antibiotic use and prognoses of the patients were analyzed.

RESULTS

Higher positivity rates were observed with mNGS versus CMTs for both PD fluid (90.0% vs. 48.3%, p < 0.005) and plasma (76.7% vs. 1.6%, p < 0.005). 90% of enrolled patients had clues of suspected pathogens combining mNGS and CMT methods. Gram-negative pathogens consist of most intra-abdominal pathogens, including a great variety of anaerobes represented by Bacteroides and Clostridium. Patients with matched plasma- and PD-mNGS results had higher mortality and sepsis severity. Reduced usage of carbapenem (30.0% vs. 49.4%, p < 0.05) and duration of anti-MRSA treatment (5.1 ± 3.3 vs. 7.0 ± 8.4 days, p < 0.05) was shown in the mNGS group in our study.

CONCLUSIONS

Pairwise plasma and PD fluid mNGS improves microbiological diagnosis compared to CMTs for acute IAI. Combining plasma and PD mNGS could predict poor prognosis. mNGS may enable optimize empirical antibiotic use.

Investigating the influence of excavating a tunnel undercrossing an existing tunnel at zero distance

In urban areas with limited underground space, the new tunnel construction introduces additional loads and displacements to existing tunnels, raising serious safety concerns. These concerns become particularly pronounced in the case of closely undercrossing excavation at zero-distance. The conventional elastic foundation beam model, which assumes constant reaction coefficients for the subgrade, fails to account for foundation loss. In this study, the existing tunnel is modeled as an Euler-Bernoulli beam supported by the Pasternak elastic foundation, and the foundation loss caused by zero-distance undercrossing excavations is considered. Furthermore, an analytical solution is proposed to evaluate the mechanical response in segments, by establishing governing differential equations and boundary conditions for the excavation and neutral zones, and underpinning loads are also considered. The analytical solution is validated in two case studies. Finally, a parametric analysis is performed to explore the influence of various parameters on the mechanical response of the existing tunnel.

Comparison and evaluation of overcoring and hydraulic fracturing stress measurements

The stress measurements determined by both the overcoring (OC) and hydraulic fracturing (HF) methods in the Shuichang iron mine and Sanshandao gold mine were compared and evaluated, respectively. The results indicate that the independent OC and HF data in the two mines reveal the same dominant faulting stress regime. The σH orientations derived from the OC and HF methods in the Shuichang iron mine are dominantly oriented in the N81.1°W-N89.4°W and N77.0°E-N88.0°E, respectively, and the σH orientations yielded from the OC and HF techniques in the Sanshandao gold mine are predominantly in the N30°W-N90°W and N55.5°W-N60.4°W, respectively; hence, the σH orientations obtained by the two different methods in the two mines are comparatively similar. In addition, the shapes of the probability density diagrams using an improved Bayesian regression approach of the three principal stresses measured by the OC and HF methods in the same mine are quite similar, and all the obtained Kolmogorov-Smirnov test p-values are larger than the selected significance level of 0.01, indicating that the stress data interpreted by the two methods approximately follow the same distribution law. Thus, the performance of the two techniques and the reliability of the measured data are satisfactory.

Effects of Lactobacillus-fermented low-protein diets on the growth performance, nitrogen excretion, fecal microbiota and metabolomic profiles of finishing pigs

This study investigated the effects of Lactobacillus-fermented low-protein diet on the growth performance, nitrogen balance, fecal microbiota, and metabolomic profiles of finishing pigs. A total of 90 finishing pigs were assigned to one of three dietary treatments including a normal protein diet (CON) as well as two experimental diets in which a low-protein diet supplemented with 0 (LP) or 1% Lactobacillus-fermented low-protein feed (FLP). In comparison with CON, the LP and FLP significantly increased average daily gain (P = 0.044), significantly decreased feed to gain ratio (P = 0.021), fecal nitrogen (P < 0.01), urine nitrogen (P < 0.01), and total nitrogen (P < 0.01), respectively. The LP group exhibited increased abundances of unclassified_f_Selenomonadaceae, Coprococcus, Faecalibacterium, and Butyricicoccus, while the abundances of Verrucomicrobiae, Verrucomicrobiales, Akkermansiaceae, and Akkermansia were enriched in the FLP group. Low-protein diet-induced metabolic changes were enriched in sesquiterpenoid and triterpenoid biosynthesis and Lactobacillus-fermented low-protein feed-induced metabolic changes were enriched in phenylpropanoid biosynthesis and arginine biosynthesis. Overall, low-protein diet and Lactobacillus-fermented low-protein diet improved the growth performance and reduce nitrogen excretion, possibly via altering the fecal microbiota and metabolites in the finishing pigs. The present study provides novel ideas regarding the application of the low-protein diet and Lactobacillus-fermented low-protein diet in swine production.

Targeted delivery of MerTK protein via cell membrane engineered nanoparticle enhances efferocytosis and attenuates atherosclerosis in diabetic ApoE-/- Mice

BACKGROUND

Clearance of apoptotic cells by efferocytosis is crucial for prevention of atherosclerosis progress, and impaired efferocytosis contributes to the aggravated atherosclerosis.

RESULTS

In this study, we found that diabetic ApoE-/- mice showed aggravated atherosclerosis as hyperglycemia damaged the efferocytosis capacity at least partially due to decreased expression of Mer tyrosine kinase (MerTK) on macrophages. To locally restore MerTK in the macrophages in the plaque, hybrid membrane nanovesicles (HMNVs) were thus developed. Briefly, cell membrane from MerTK overexpressing RAW264.7 cell and transferrin receptor (TfR) overexpressing HEK293T cell were mixed with DOPE polymers to produce nanovesicles designated as HMNVs. HMNVs could fuse with the recipient cell membrane and thus increased MerTK in diabetic macrophages, which in turn restored the efferocytosis capacity. Upon intravenous administration into diabetic ApoE-/- mice, superparamagnetic iron oxide nanoparticles (SMN) decorated HMNVs accumulated at the aorta site significantly under magnetic navigation, where the recipient macrophages cleared the apoptotic cells efficiently and thus decreased the inflammation.

CONCLUSIONS

 Our study indicates that MerTK decrease in macrophages contributes to the aggravated atherosclerosis in diabetic ApoE-/- mice and regional restoration of MerTK in macrophages of the plaque via HMNVs could be a promising therapeutic approach.

Clinically relevant plasma proteome for adiposity depots: evidence from systematic mendelian randomization and colocalization analyses

BACKGROUND

The accumulation of visceral and ectopic fat comprise a major cause of cardiometabolic diseases. However, novel drug targets for reducing unnecessary visceral and ectopic fat are still limited. Our study aims to provide a comprehensive investigation of the causal effects of the plasma proteome on visceral and ectopic fat using Mendelian randomization (MR) approach.

METHODS

We performed two-sample MR analyses based on five large genome-wide association study (GWAS) summary statistics of 2656 plasma proteins, to screen for causal associations of these proteins with traits of visceral and ectopic fat in over 30,000 participants of European ancestry, as well as to assess mediation effects by risk factors of outcomes. The colocalization analysis was conducted to examine whether the identified proteins and outcomes shared casual variants.

RESULTS

Genetically predicted levels of 14 circulating proteins were associated with visceral and ectopic fat (P < 4.99 × 10- 5, at a Bonferroni-corrected threshold). Colocalization analysis prioritized ten protein targets that showed effect on outcomes, including FST, SIRT2, DNAJB9, IL6R, CTSA, RGMB, PNLIPRP1, FLT4, PPY and IL6ST. MR analyses revealed seven risk factors for visceral and ectopic fat (P < 0.0024). Furthermore, the associations of CTSA, DNAJB9 and IGFBP1 with primary outcomes were mediated by HDL-C and SHBG. Sensitivity analyses showed little evidence of pleiotropy.

CONCLUSIONS

Our study identified candidate proteins showing putative causal effects as potential therapeutic targets for visceral and ectopic fat accumulation and outlined causal pathways for further prevention of downstream cardiometabolic diseases.

Mulberry branch fiber improved lipid metabolism and egg yolk fatty acid composition of laying hens via the enterohepatic axis

BACKGROUND

The utilization of mulberry branch fiber (MF), the largest by-product of the sericulture industry, is an important issue. Supplementation with MF as a dietary fiber for poultry may serve as a useful application. However, little is known about the effects of MF on liver lipid metabolism and egg yolk fatty acid composition of laying hens and their underlying mechanisms. In this study, we performed a multi-omics investigation to explore the variations in liver lipid metabolism, egg yolk fatty acid composition, gut microbiota, and the associations among them induced by dietary MF in laying hens.

RESULTS

Dietary MF had no harmful effects on the laying performance or egg quality in laying hens. The enzyme activities associated with lipid metabolism in the liver were altered by the addition of 5% MF, resulting in reduced liver fat accumulation. Furthermore, dietary 5% MF induced the variation in the fatty acid profiles of egg yolk, and increased the polyunsaturated fatty acid (PUFA) content. We observed a significant reduction in the diversity of both gut bacteria and changes in their compositions after the addition of MF. Dietary MF significantly increased the abundance of genes involved in fatty acid biodegradation, and short-chain fatty acids biosynthesis in the gut microbiota of laying hens. The significant correlations were observed between the liver lipid metabolism enzyme activities of hepatic lipase, lipoprotein lipase, and total esterase with gut microbiota, including negative correlations with gut microbiota diversity, and multiple correlations with gut bacteria and viruses. Moreover, various correlations between the contents of PUFAs and monounsaturated fatty acids in egg yolk with the gut microbiota were obtained. Based on partial-least-squares path modeling integrated with the multi-omics datasets, we deduced the direct effects of liver enzyme activities and gut bacterial compositions on liver fat content and the roles of liver enzyme activities and gut bacterial diversity on egg yolk fatty acid composition.

CONCLUSIONS

The results indicate that dietary MF is beneficial to laying hens as it reduces the liver fat and improves egg yolk fatty acid composition through the enterohepatic axis. Video Abstract.

Successful ECMO treatment in patients with cerebral hemorrhage and PROC gene mutation associated with VTE: a case report

In this report, we report a case of a middle-aged male, admitted to the ICU with cerebral hemorrhage resulting from a severe high-altitude fall. The patient encountered significant challenges in oxygenation index correction, attributed to extensive embolism in both the primary and branch pulmonary arteries. Consequently, the patient underwent an immediate initiation of veno-arterial extracorporeal membrane oxygenation (VA-ECMO) therapy, persisting for 20 days. During this treatment period, a mutation in the protein C (PROC) gene was identified. The medical team meticulously navigated the delicate balance between anticoagulation and bleeding risks. Eventually, the patient was successfully weaned off VA-ECMO and subsequently discharged. This report aims to delve into the etiology and therapeutic approaches of this uncommon case, with the intention of offering insightful reference for managing similar clinical scenarios in the future.

Bacteria-driven nanosonosensitizer delivery system for enhanced breast cancer treatment through sonodynamic therapy-induced immunogenic cell death

BACKGROUND

Sonodynamic therapy (SDT) has shown promise as a non-invasive cancer treatment due to its local effects and excellent tissue penetration. However, the limited accumulation of sonosensitizers at the tumor site hinders its therapeutic efficacy. Although nanosonosensitizers have improved local tumor accumulation through passive targeting via the enhanced permeability and retention effect (EPR), achieving sufficient accumulation and penetration into tumors remains challenging due to tumor heterogeneity and inaccurate targeting. Bacteria have become a promising biological carrier due to their unique characteristic of active targeting and deeper penetration into the tumor.

METHODS

In this study, we developed nanosonosensitizers consisting of sonosensitizer, hematoporphyrin monomethyl ether (HMME), and perfluoro-n-pentane (PFP) loaded poly (lactic-co-glycolic) acid (PLGA) nanodroplets (HPNDs). These HPNDs were covalently conjugated onto the surface of Escherichia coli Nissle 1917 (EcN) using carbodiimine chemistry. EcN acted as an active targeting micromotor for efficient transportation of the nanosonosensitizers to the tumor site in triple-negative breast cancer (TNBC) treatment. Under ultrasound cavitation, the HPNDs were disrupted, releasing HMME and facilitating its uptakes by cancer cells. This process induced reactive oxygen species (ROS)-mediated cell apoptosis and immunogenic cell death (ICD) in vitro and in vivo.

RESULTS

Our bacteria-driven nanosonosensitizer delivery system (HPNDs@EcN) achieved superior tumor localization of HMME in vivo compared to the group treated with only nanosonosensitizers. This enhanced local accumulation further improved the therapeutic effect of SDT induced-ICD therapeutic effect and inhibited tumor metastasis under ultrasound stimulation.

CONCLUSIONS

Our research demonstrates the potential of this ultrasound-responsive bacteria-driven nanosonosensitizer delivery system for SDT in TNBC. The combination of targeted delivery using bacteria and nanosonosensitizer-based therapy holds promise for achieving improved treatment outcomes by enhancing local tumor accumulation and stimulating ICD.

Peripheral extracellular vesicles in neurodegeneration: pathogenic influencers and therapeutic vehicles

Neurodegenerative diseases (NDDs) such as Alzheimer's disease, Parkinson's disease, and amyotrophic lateral sclerosis epitomize a class of insidious and relentless neurological conditions that are difficult to cure. Conventional therapeutic regimens often fail due to the late onset of symptoms, which occurs well after irreversible neurodegeneration has begun. The integrity of the blood-brain barrier (BBB) further impedes efficacious drug delivery to the central nervous system, presenting a formidable challenge in the pharmacological treatment of NDDs. Recent scientific inquiries have shifted focus toward the peripheral biological systems, investigating their influence on central neuropathology through the lens of extracellular vesicles (EVs). These vesicles, distinguished by their ability to breach the BBB, are emerging as dual operatives in the context of NDDs, both as conveyors of pathogenic entities and as prospective vectors for therapeutic agents. This review critically summarizes the burgeoning evidence on the role of extracerebral EVs, particularly those originating from bone, adipose tissue, and gut microbiota, in modulating brain pathophysiology. It underscores the duplicity potential of peripheral EVs as modulators of disease progression and suggests their potential as novel vehicles for targeted therapeutic delivery, positing a transformative impact on the future landscape of NDD treatment strategies. Search strategy A comprehensive literature search was conducted using PubMed, Web of Science, and Scopus from January 2000 to December 2023. The search combined the following terms using Boolean operators: "neurodegenerative disease" OR "Alzheimer's disease" OR "Parkinson's disease" OR "Amyotrophic lateral sclerosis" AND "extracellular vesicles" OR "exosomes" OR "outer membrane vesicles" AND "drug delivery systems" AND "blood-brain barrier". MeSH terms were employed when searching PubMed to refine the results. Studies were included if they were published in English, involved human subjects, and focused on the peripheral origins of EVs, specifically from bone, adipose tissue, and gut microbiota, and their association with related diseases such as osteoporosis, metabolic syndrome, and gut dysbiosis. Articles were excluded if they did not address the role of EVs in the context of NDDs or did not discuss therapeutic applications. The titles and abstracts of retrieved articles were screened using a dual-review process to ensure relevance and accuracy. The reference lists of selected articles were also examined to identify additional relevant studies.

Preoperative nomogram for predicting spread through air spaces in clinical-stage IA non-small cell lung cancer using 18F-fluorodeoxyglucose positron emission tomography/computed tomography

PURPOSE

This study aims to assess the predictive value of 18F-fluorodeoxyglucose positron emission tomography/computed tomography (18F-FDG PET/CT) radiological features and the maximum standardized uptake value (SUVmax) in determining the presence of spread through air spaces (STAS) in clinical-stage IA non-small cell lung cancer (NSCLC).

METHODS

A retrospective analysis was conducted on 180 cases of NSCLC with postoperative pathological assessment of STAS status, spanning from September 2019 to September 2023. Of these, 116 cases from hospital one comprised the training set, while 64 cases from hospital two formed the testing set. The clinical information, tumor SUVmax, and 13 related CT features were analyzed. Subgroup analysis was carried out based on tumor density type. In the training set, univariable and multivariable logistic regression analyses were employed to identify the most significant variables. A multivariable logistic regression model was constructed and the corresponding nomogram was developed to predict STAS in NSCLC, and its diagnostic efficacy was evaluated in the testing set.

RESULTS

SUVmax, consolidation-to-tumor ratio (CTR), and lobulation sign emerged as the best combination of variables for predicting STAS in NSCLC. Among these, SUVmax and CTR were identified as independent predictors for STAS prediction. The constructed prediction model demonstrated area under the curve (AUC) values of 0.796 and 0.821 in the training and testing sets, respectively. Subgroup analysis revealed a 2.69 times higher STAS-positive rate in solid nodules compared to part-solid nodules. SUVmax was an independent predictor for predicting STAS in solid nodular NSCLC, while CTR and an emphysema background were independent predictors for STAS in part-solid nodular NSCLC.

CONCLUSION

Our nomogram based on preoperative 18F-FDG PET/CT radiological features and SUVmax effectively predicts STAS status in clinical-stage IA NSCLC. Furthermore, our study highlights that metabolic parameters and CT variables associated with STAS differ between solid and part-solid nodular NSCLC.

Intestinal Mucosal Immune Barrier: A Powerful Firewall Against Severe Acute Pancreatitis-Associated Acute Lung Injury via the Gut-Lung Axis

The pathogenesis of severe acute pancreatitis-associated acute lung injury (SAP-ALI), which is the leading cause of mortality among hospitalized patients in the intensive care unit, remains incompletely elucidated. The intestinal mucosal immune barrier is a crucial component of the intestinal epithelial barrier, and its aberrant activation contributes to the induction of sustained pro-inflammatory immune responses, paradoxical intercellular communication, and bacterial translocation. In this review, we firstly provide a comprehensive overview of the composition of the intestinal mucosal immune barrier and its pivotal roles in the pathogenesis of SAP-ALI. Secondly, the mechanisms of its crosstalk with gut microbiota, which is called gut-lung axis, and its effect on SAP-ALI were summarized. Finally, a number of drugs that could enhance the intestinal mucosal immune barrier and exhibit potential anti-SAP-ALI activities were presented, including probiotics, glutamine, enteral nutrition, and traditional Chinese medicine (TCM). The aim is to offer a theoretical framework based on the perspective of the intestinal mucosal immune barrier to protect against SAP-ALI.

MiR-574-5p activates human TLR8 to promote autoimmune signaling and lupus

Endosomal single-stranded RNA-sensing Toll-like receptor-7/8 (TLR7/8) plays a pivotal role in inflammation and immune responses and autoimmune diseases. However, the mechanisms underlying the initiation of the TLR7/8-mediated autoimmune signaling remain to be fully elucidated. Here, we demonstrate that miR-574-5p is aberrantly upregulated in tissues of lupus prone mice and in the plasma of lupus patients, with its expression levels correlating with the disease activity. miR-574-5p binds to and activates human hTLR8 or its murine ortholog mTlr7 to elicit a series of MyD88-dependent immune and inflammatory responses. These responses include the overproduction of cytokines and interferons, the activation of STAT1 signaling and B lymphocytes, and the production of autoantigens. In a transgenic mouse model, the induction of miR-574-5p overexpression is associated with increased secretion of antinuclear and anti-dsDNA antibodies, increased IgG and C3 deposit in the kidney, elevated expression of inflammatory genes in the spleen. In lupus-prone mice, lentivirus-mediated silencing of miR-574-5p significantly ameliorates major symptoms associated with lupus and lupus nephritis. Collectively, these results suggest that the miR-574-5p-hTLR8/mTlr7 signaling is an important axis of immune and inflammatory responses, contributing significantly to the development of lupus and lupus nephritis.

Epiberberine: a potential rumen microbial urease inhibitor to reduce ammonia release screened by targeting UreG

Rumen microbial urease inhibitors have been proposed for regulating nitrogen emission and improving nitrogen utilization efficiency in ruminant livestock industry. However, studies on plant-derived natural inhibitors of rumen microbial urease are limited. Urease accessory protein UreG, plays a crucial role in facilitating urease maturation, is a new target for design of urease inhibitor. The objective of this study was to select the potential effective inhibitor of rumen microbial urease from major protoberberine alkaloids in Rhizoma Coptidis by targeting UreG. Our results showed that berberine chloride and epiberberine exerted superior inhibition potential than other alkaloids based on GTPase activity study of UreG. Berberine chloride inhibition of UreG was mixed type, while inhibition kinetics type of epiberberine was uncompetitive. Furthermore, epiberberine was found to be more effective than berberine chloride in inhibiting the combination of nickel towards UreG and inducing changes in the second structure of UreG. Molecular modeling provided the rational structural basis for the higher inhibition potential of epiberberine, amino acid residues in G1 motif and G3 motif of UreG formed interactions with D ring of berberine chloride, while interacted with A ring and D ring of epiberberine. We further demonstrated the efficacy of epiberberine in the ruminal microbial fermentation with low ammonia release and urea degradation. In conclusion, our study clearly indicates that epiberberine is a promising candidate as a safe and effective inhibitor of rumen microbial urease and provides an optimal strategy and suitable feed additive for regulating nitrogen excretion in ruminants in the future. KEY POINTS: • Epiberberine is the most effective inhibitor of rumen urease from Rhizoma Coptidis. • Urease accessory protein UreG is an effective target for design of urease inhibitor. • Epiberberine may be used as natural feed additive to reducing NH3 release in ruminants.

Genome-wide investigation of UDP-Glycosyltransferase family in Tartary buckwheat (Fagopyrum tataricum)

BACKGROUND

Tartary buckwheat (Fagopyrum tataricum) belongs to Polygonaceae family and has attracted increasing attention owing to its high nutritional value. UDP-glycosyltransferases (UGTs) glycosylate a variety of plant secondary metabolites to control many metabolic processes during plant growth and development. However, there have been no systematic reports of UGT superfamily in F. tataricum.

RESULTS

We identified 173 FtUGTs in F. tataricum based on their conserved UDPGT domain. Phylogenetic analysis of FtUGTs with 73 Arabidopsis UGTs clustered them into 21 families. FtUGTs from the same family usually had similar gene structure and motif compositions. Most of FtUGTs did not contain introns or had only one intron. Tandem repeats contributed more to FtUGTs amplification than segmental duplications. Expression analysis indicates that FtUGTs are widely expressed in various tissues and likely play important roles in plant growth and development. The gene expression analysis response to different abiotic stresses showed that some FtUGTs were involved in response to drought and cadmium stress. Our study provides useful information on the UGTs in F. tataricum, and will facilitate their further study to better understand their function.

CONCLUSIONS

Our results provide a theoretical basis for further exploration of the functional characteristics of FtUGTs and for understanding the growth, development, and metabolic model in F. tataricum.

Effect of adaptive laboratory evolution of engineered Escherichia coli in acetate on the biosynthesis of succinic acid from glucose in two-stage cultivation

Escherichia coli MLB (MG1655 ΔpflB ΔldhA), which can hardly grow on glucose with little succinate accumulation under anaerobic conditions. Two-stage fermentation is a fermentation in which the first stage is used for cell growth and the second stage is used for product production. The ability of glucose consumption and succinate production of MLB under anaerobic conditions can be improved significantly by using acetate as the solo carbon source under aerobic condition during the two-stage fermentation. Then, the adaptive laboratory evolution (ALE) of growing on acetate was applied here. We assumed that the activities of succinate production related enzymes might be further improved in this study. E. coli MLB46-05 evolved from MLB and it had an improved growth phenotype on acetate. Interestingly, in MLB46-05, the yield and tolerance of succinic acid in the anaerobic condition of two-stage fermentation were improved significantly. According to transcriptome analysis, upregulation of the glyoxylate cycle and the activity of stress regulatory factors are the possible reasons for the elevated yield. And the increased tolerance to acetate made it more tolerant to high concentrations of glucose and succinate. Finally, strain MLB46-05 produced 111 g/L of succinic acid with a product yield of 0.74 g/g glucose. SYNOPSIS.

Multiple phenotype association tests based on sliced inverse regression

BACKGROUND

Joint analysis of multiple phenotypes in studies of biological systems such as Genome-Wide Association Studies is critical to revealing the functional interactions between various traits and genetic variants, but growth of data in dimensionality has become a very challenging problem in the widespread use of joint analysis. To handle the excessiveness of variables, we consider the sliced inverse regression (SIR) method. Specifically, we propose a novel SIR-based association test that is robust and powerful in testing the association between multiple predictors and multiple outcomes.

RESULTS

We conduct simulation studies in both low- and high-dimensional settings with various numbers of Single-Nucleotide Polymorphisms and consider the correlation structure of traits. Simulation results show that the proposed method outperforms the existing methods. We also successfully apply our method to the genetic association study of ADNI dataset. Both the simulation studies and real data analysis show that the SIR-based association test is valid and achieves a higher efficiency compared with its competitors.

CONCLUSION

Several scenarios with low- and high-dimensional responses and genotypes are considered in this paper. Our SIR-based method controls the estimated type I error at the pre-specified level α .

High-Temperature Tolerance Protein Engineering through Deep Evolution

Protein engineering aimed at increasing temperature tolerance through iterative mutagenesis and high-throughput screening is often labor-intensive. Here, we developed a deep evolution (DeepEvo) strategy to engineer protein high-temperature tolerance by generating and selecting functional sequences using deep learning models. Drawing inspiration from the concept of evolution, we constructed a high-temperature tolerance selector based on a protein language model, acting as selective pressure in the high-dimensional latent spaces of protein sequences to enrich those with high-temperature tolerance. Simultaneously, we developed a variant generator using a generative adversarial network to produce protein sequence variants containing the desired function. Afterward, the iterative process involving the generator and selector was executed to accumulate high-temperature tolerance traits. We experimentally tested this approach on the model protein glyceraldehyde 3-phosphate dehydrogenase, obtaining 8 variants with high-temperature tolerance from just 30 generated sequences, achieving a success rate of over 26%, demonstrating the high efficiency of DeepEvo in engineering protein high-temperature tolerance.

Ancient Mitogenomes Reveal the Maternal Genetic History of East Asian Dogs

Recent studies have suggested that dogs were domesticated during the Last Glacial Maximum (LGM) in Siberia, which contrasts with previous proposed domestication centers (e.g. Europe, the Middle East, and East Asia). Ancient DNA provides a powerful resource for the study of mammalian evolution and has been widely used to understand the genetic history of domestic animals. To understand the maternal genetic history of East Asian dogs, we have made a complete mitogenome dataset of 120 East Asian canids from 38 archaeological sites, including 102 newly sequenced from 12.9 to 1 ka BP (1,000 years before present). The majority (112/119, 94.12%) belonged to haplogroup A, and half of these (55/112, 49.11%) belonged to sub-haplogroup A1b. Most existing mitochondrial haplogroups were present in ancient East Asian dogs. However, mitochondrial lineages in ancient northern dogs (northeastern Eurasia and northern East Asia) were deeper and older than those in southern East Asian dogs. Results suggests that East Asian dogs originated from northeastern Eurasian populations after the LGM, dispersing in two possible directions after domestication. Western Eurasian (Europe and the Middle East) dog maternal ancestries genetically influenced East Asian dogs from approximately 4 ka BP, dramatically increasing after 3 ka BP, and afterwards largely replaced most primary maternal lineages in northern East Asia. Additionally, at least three major mitogenome sub-haplogroups of haplogroup A (A1a, A1b, and A3) reveal at least two major dispersal waves onto the Qinghai-Tibet Plateau in ancient times, indicating eastern (A1b and A3) and western (A1a) Eurasian origins.

Reforming solid tumor treatment: the emerging potential of smaller format antibody-drug conjugate

In recent years, substantial therapeutic efficacy of antibody-drug conjugates (ADCs) has been validated through approvals of 16 ADCs for the treatment of malignant tumors. However, realization of the maximum clinical use of ADCs requires surmounting extant challenges, mainly the limitations in tumor penetration capabilities when targeting solid tumors. To resolve the hurdle of suboptimal tumor penetration, miniaturized antibody fragments with engineered formats have been harnessed for ADC assembly. By virtue of their reduced molecular sizes, antibody fragment-drug conjugates hold considerable promise for efficacious delivery of cytotoxic agents, thus conferring superior therapeutic outcomes. This review will focus on current advancements in novel ADC development utilizing smaller antibody formats from ~6 to 80 kDa, with particular emphasis on single-domain antibodies, which have been widely applied in novel ADC design. Additionally, strategies to optimize clinical translation are discussed, including half-life extension, acceleration of internalization, and reduction of immunogenic potential.

Age-specific difference in the temporal relationships between updated cardiovascular health construct and arterial stiffness in middle-aged and older adults

Previous studies have found that the association between modifiable risk factors and arterial stiffness varied with age. We aimed to explore the age-specific difference in the relationship between new cardiovascular health (CVH) score and arterial stiffness and further detected the age-specific temporal relationships in a prospective cohort study. During a median 4.3 years follow-up, 3757 participants were recruited in this study. A modified AHA "Life's Essential 8" construct (mLE8 with lacking information on diet habits) was used to evaluate CVH. Branchial-ankle pulse wave velocity (baPWV) was measured to assess arterial stiffness. Data were analyzed with logistic regression models, restricted cubic splines (RCS), and cross-lagged path analysis (age < 60 vs. age ≥ 60). In age-stratified analysis, moderate (OR = 2.21, 95% CI 1.11-4.43) and low (OR = 3.37, 95% CI 1.63-7.00) CVH were related with a higher incidence of elevated baPWV compared to high CVH in middle-aged adults, while this association was not detected in older adults. RCS curve showed a steeper linear association between CVH score and elevated baPWV in middle-aged adults than older individuals. In the cross-lagged path analysis, the decline in CVH score preceded the increment in arterial stiffness in middle-aged adults, but they appeared to alter simultaneously in older adults. Our study detected an age-specific difference in the relationship between mLE8 CVH score and elevated baPWV and showed that low CVH preceded alterations of baPWV in middle-aged adults, suggesting the importance of improvement in CVH during the early stage of the lifespan.

Porcine reproductive and respiratory syndrome virus 2 hijacks CMA-mediated lipolysis through upregulation of small GTPase RAB18

RAB GTPases (RABs) control intracellular membrane trafficking with high precision. In the present study, we carried out a short hairpin RNA (shRNA) screen focused on a library of 62 RABs during infection with porcine reproductive and respiratory syndrome virus 2 (PRRSV-2), a member of the family Arteriviridae. We found that 13 RABs negatively affect the yield of PRRSV-2 progeny virus, whereas 29 RABs have a positive impact on the yield of PRRSV-2 progeny virus. Further analysis revealed that PRRSV-2 infection transcriptionally regulated RAB18 through RIG-I/MAVS-mediated canonical NF-κB activation. Disrupting RAB18 expression led to the accumulation of lipid droplets (LDs), impaired LDs catabolism, and flawed viral replication and assembly. We also discovered that PRRSV-2 co-opts chaperone-mediated autophagy (CMA) for lipolysis via RAB18, as indicated by the enhanced associations between RAB18 and perlipin 2 (PLIN2), CMA-specific lysosomal associated membrane protein 2A (LAMP2A), and heat shock protein family A (Hsp70) member 8 (HSPA8/HSC70) during PRRSV-2 infection. Knockdown of HSPA8 and LAMP2A impacted on the yield of PRRSV-2 progeny virus, implying that the virus utilizes RAB18 to promote CMA-mediated lipolysis. Importantly, we determined that the C-terminal domain (CTD) of HSPA8 could bind to the switch II domain of RAB18, and the CTD of PLIN2 was capable of associating with HSPA8, suggesting that HSPA8 facilitates the interaction between RAB18 and PLIN2 in the CMA process. In summary, our findings elucidate how PRRSV-2 hijacks CMA-mediated lipid metabolism through innate immune activation to enhance the yield of progeny virus, offering novel insights for the development of anti-PRRSV-2 treatments.

TPMA: A two pointers meta-alignment tool to ensemble different multiple nucleic acid sequence alignments

Accurate multiple sequence alignment (MSA) is imperative for the comprehensive analysis of biological sequences. However, a notable challenge arises as no single MSA tool consistently outperforms its counterparts across diverse datasets. Users often have to try multiple MSA tools to achieve optimal alignment results, which can be time-consuming and memory-intensive. While the overall accuracy of certain MSA results may be lower, there could be local regions with the highest alignment scores, prompting researchers to seek a tool capable of merging these locally optimal results from multiple initial alignments into a globally optimal alignment. In this study, we introduce Two Pointers Meta-Alignment (TPMA), a novel tool designed for the integration of nucleic acid sequence alignments. TPMA employs two pointers to partition the initial alignments into blocks containing identical sequence fragments. It selects blocks with the high sum of pairs (SP) scores to concatenate them into an alignment with an overall SP score superior to that of the initial alignments. Through tests on simulated and real datasets, the experimental results consistently demonstrate that TPMA outperforms M-Coffee in terms of aSP, Q, and total column (TC) scores across most datasets. Even in cases where TPMA's scores are comparable to M-Coffee, TPMA exhibits significantly lower running time and memory consumption. Furthermore, we comprehensively assessed all the MSA tools used in the experiments, considering accuracy, time, and memory consumption. We propose accurate and fast combination strategies for small and large datasets, which streamline the user tool selection process and facilitate large-scale dataset integration. The dataset and source code of TPMA are available on GitHub (https://github.com/malabz/TPMA).

Integrin α3 is required for high-frequency repetitive transcranial magnetic stimulation-induced glutamatergic synaptic transmission in mice with ischemia

BACKGROUND

Repetitive transcranial magnetic stimulation (rTMS) is an effective therapy in post-stroke motor recovery. However, the underlying mechanisms of rTMS regulates long-lasting changes with synaptic transmission and glutamate receptors function (including AMPARs or NMDARs) remains unclear.

METHODS

Mice were received 10-Hz rTMS treatment once daily on the third day after photothrombotic (PT) stroke for 18 days. Motor behaviors and the Western blot were used to evaluate the therapeutic efficacy of 10-Hz rTMS in the mice with PT model. Moreover, we used wild-type (WT) and NEX-α3-/- mice to further explore the 10-Hz rTMS effect.

RESULTS

We found that 10-Hz rTMS improved the post-stroke motor performance in the PT mice. Moreover, the levels of AMPAR, vGlut1, and integrin α3 in the peri-infarct were significantly increased in the rTMS group. In contrast, 10-Hz rTMS did not induce these aforementioned effects in NEX-α3-/- mice. The amplitude of AMPAR-mediated miniature excitatory postsynaptic currents (EPSCs) and evoked EPSCs was increased in the WT + rTMS group, but did not change in NEX-α3-/- mice with rTMS.

CONCLUSIONS

In this study, 10-Hz rTMS improved the glutamatergic synaptic transmission in the peri-infract cortex through effects on integrin α3 and AMPARs, which resulted in motor function recovery after stroke.

Exome sequencing identifies homozygous variants in MBOAT7 associated with neurodevelopmental disorder

Intellectual disability (ID) is a large group of neurodevelopmental disorders characterized by a congenital limitation in intellectual functioning (reasoning, learning, and problem solving), adaptive behavior (conceptual, social, and practical skills), originated at birth and manifested before the age of 18. By whole exome sequencing of five consanguineous Pakistani families presenting hallmark features of ID, global developmental delay, aggressive and self-injurious behaviors, microcephaly, febrile seizures and facial dysmorphic features, we identified three novel homozygous missense variants (NM_024298.5: c.588G > T; p.Trp196Cys, c.736 T > C; p.Tyr246His and c.524A > C; p. Asp175Ala) and one rare homozygous in-frame deletion variant (c.758_778del;p.Glu253_Ala259del) in membrane-bound O-acyltransferase family member 7 (MBOAT7) gene previously associated with autosomal recessive neurodevelopmental disorder. The segregation of the variants was validated by Sanger sequencing in all family members. In silico homology modeling of wild-type and mutated proteins revealed substantial changes in the structure of both proteins, indicating a possible effect on function. The identification and validation of new pathogenic MBOAT7 variants in five cases of autosomal recessive ID further highlight the importance of this genes in proper brain function and development.

Plant-LncPipe: a computational pipeline providing significant improvement in plant lncRNA identification

Long non-coding RNAs (lncRNAs) play essential roles in various biological processes, such as chromatin remodeling, post-transcriptional regulation, and epigenetic modifications. Despite their critical functions in regulating plant growth, root development, and seed dormancy, the identification of plant lncRNAs remains a challenge due to the scarcity of specific and extensively tested identification methods. Most mainstream machine learning-based methods used for plant lncRNA identification were initially developed using human or other animal datasets, and their accuracy and effectiveness in predicting plant lncRNAs have not been fully evaluated or exploited. To overcome this limitation, we retrained several models, including CPAT, PLEK, and LncFinder, using plant datasets and compared their performance with mainstream lncRNA prediction tools such as CPC2, CNCI, RNAplonc, and LncADeep. Retraining these models significantly improved their performance, and two of the retrained models, LncFinder-plant and CPAT-plant, alongside their ensemble, emerged as the most suitable tools for plant lncRNA identification. This underscores the importance of model retraining in tackling the challenges associated with plant lncRNA identification. Finally, we developed a pipeline (Plant-LncPipe) that incorporates an ensemble of the two best-performing models and covers the entire data analysis process, including reads mapping, transcript assembly, lncRNA identification, classification, and origin, for the efficient identification of lncRNAs in plants. The pipeline, Plant-LncPipe, is available at: https://github.com/xuechantian/Plant-LncRNA-pipline.

Reliability and validity of a graphical computerized adaptive test Longshi scale for rapid assessment of activities of daily living in stroke survivors

Stroke survivors frequently experience difficulties in daily activities, such as bathing, feeding, and mobility. This study aimed to evaluate the reliability and validity of a computer-adaptive test-Longshi scale (CAT-LS) for assessing activities of daily living (ADL) in stroke survivors. This cross-sectional study collected data using an electronic application. The ADL function of stroke survivors in rehabilitation departments of hospitals was assessed using both the CAT-LS and BI. Correlations between the CAT-LS and Barthel index (BI) and concurrent validity were evaluated using Pearson's correlation test and multiple linear regression. Interrater reliability was evaluated using the intraclass correlation coefficient based on a two-way random effect. The internal consistency of the CAT-LS was assessed using Cronbach's coefficient (α) and corrected item-total correlations. Overall, 103 medical institutions in China were used in this study. In total, 7151 patients with stroke were included in this study. The CAT-LS classified patients into three ADL groups (bedridden, domestic, and community) with significantly different BI scores (P < 0.05). The CAT-LS results obtained using the decision-tree scoring model were consistent with the scores for each BI item. A strong correlation was observed between CAT-LS and BI (Pearson's r: 0.6-0.894, P < 0.001). The CAT-LS demonstrated good internal consistency (Cronbach's α, 0.803-0.894) and interrater reliability (ICC, 0.928-0.979). CAT-LS is time-efficient and requires < 1 min to administer. The CAT-LS is a reliable and valid tool for assessing ADL function in stroke survivors and can provide rapid and accurate assessments that reduce the burden on healthcare professionals. Further validation of this tool in other populations and settings is necessary.Study registration number: No.: ChiCTR2000034067; http://www.chictr.org.cn/showproj.aspx?proj=54770 .

CT-Based Intratumoral and Peritumoral Radiomics Nomograms for the Preoperative Prediction of Spread Through Air Spaces in Clinical Stage IA Non-small Cell Lung Cancer

The study aims to investigate the value of intratumoral and peritumoral radiomics and clinical-radiological features for predicting spread through air spaces (STAS) in patients with clinical stage IA non-small cell lung cancer (NSCLC). A total of 336 NSCLC patients from our hospital were randomly divided into the training cohort (n = 236) and the internal validation cohort (n = 100) at a ratio of 7:3, and 69 patients from the other two external hospitals were collected as the external validation cohort. Univariate and multivariate analyses were used to select clinical-radiological features and construct a clinical model. The GTV, PTV5, PTV10, PTV15, PTV20, GPTV5, GPTV10, GPTV15, and GPTV20 models were constructed based on intratumoral and peritumoral (5 mm, 10 mm, 15 mm, 20 mm) radiomics features. Additionally, the radscore of the optimal radiomics model and clinical-radiological predictors were used to construct a combined model and plot a nomogram. Lastly, the ROC curve and AUC value were used to evaluate the diagnostic performance of the model. Tumor density type (OR = 6.738) and distal ribbon sign (OR = 5.141) were independent risk factors for the occurrence of STAS. The GPTV10 model outperformed the other radiomics models, and its AUC values were 0.887, 0.876, and 0.868 in the three cohorts. The AUC values of the combined model constructed based on GPTV10 radscore and clinical-radiological predictors were 0.901, 0.875, and 0.878. DeLong test results revealed that the combined model was superior to the clinical model in the three cohorts. The nomogram based on GPTV10 radscore and clinical-radiological features exhibited high predictive efficiency for STAS status in NSCLC.

Disrupted topological organization of the default mode network in mild cognitive impairment with subsyndromal depression: A graph theoretical analysis

AIMS

Subsyndromal depression (SSD) is common in mild cognitive impairment (MCI). However, the neural mechanisms underlying MCI with SSD (MCID) are unclear. The default mode network (DMN) is associated with cognitive processes and depressive symptoms. Therefore, we aimed to explore the topological organization of the DMN in patients with MCID.

METHODS

Forty-two MCID patients, 34 MCI patients without SSD (MCIND), and 36 matched healthy controls (HCs) were enrolled. The resting-state functional connectivity of the DMN of the participants was analyzed using a graph theoretical approach. Correlation analyses of network topological metrics, depressive symptoms, and cognitive function were conducted. Moreover, support vector machine (SVM) models were constructed based on topological metrics to distinguish MCID from MCIND. Finally, we used 10 repeats of 5-fold cross-validation for performance verification.

RESULTS

We found that the global efficiency and nodal efficiency of the left anterior medial prefrontal cortex (aMPFC) of the MCID group were significantly lower than the MCIND group. Moreover, small-worldness and global efficiency were negatively correlated with depressive symptoms in MCID, and the nodal efficiency of the left lateral temporal cortex and left aMPFC was positively correlated with cognitive function in MCID. In cross-validation, the SVM model had an accuracy of 0.83 [95% CI 0.79-0.87], a sensitivity of 0.88 [95% CI 0.86-0.90], a specificity of 0.75 [95% CI 0.72-0.78] and an area under the curve of 0.88 [95% CI 0.85-0.91].

CONCLUSIONS

The coexistence of MCI and SSD was associated with the greatest disrupted topological organization of the DMN. The network topological metrics could identify MCID and serve as biomarkers of different clinical phenotypic presentations of MCI.

Paxillin phase separation promotes focal adhesion assembly and integrin signaling

Focal adhesions (FAs) are transmembrane protein assemblies mediating cell-matrix connection. Although protein liquid-liquid phase separation (LLPS) has been tied to the organization and dynamics of FAs, the underlying mechanisms remain unclear. Here, we experimentally tune the LLPS of PXN/Paxillin, an essential scaffold protein of FAs, by utilizing a light-inducible Cry2 system in different cell types. In addition to nucleating FA components, light-triggered PXN LLPS potently activates integrin signaling and subsequently accelerates cell spreading. In contrast to the homotypic interaction-driven LLPS of PXN in vitro, PXN condensates in cells are associated with the plasma membrane and modulated by actomyosin contraction and client proteins of FAs. Interestingly, non-specific weak intermolecular interactions synergize with specific molecular interactions to mediate the multicomponent condensation of PXN and are efficient in promoting FA assembly and integrin signaling. Thus, our data establish an active role of the PXN phase transition into a condensed membrane-associated compartment in promoting the assembly/maturation of FAs.

The radiomics nomogram predicts the prognosis of pancreatic cancer patients with hepatic metastasis after chemoimmunotherapy

OBJECTIVE

To construct a prognostic model based on MR features and clinical data to evaluate the progression free survival (PFS), overall survival (OS) and objective response rate (ORR) of pancreatic cancer patients with hepatic metastases who received chemoimmunotherapy.

METHODS

105 pancreatic cancer patients with hepatic metastases who received chemoimmunotherapy were assigned to the training set (n = 52), validation set (n = 22), and testing set (n = 31). Multi-lesion volume of interest were delineated, multi-sequence radiomics features were extracted, and the radiomics models for predicting PFS, OS and ORR were constructed, respectively. Clinical variables were extracted, and the clinical models for predicting PFS, OS and ORR were constructed, respectively. The nomogram was jointly constructed by radiomics model and clinical model.

RESULT

The ORR exhibits no significant correlation with either PFS or OS. The area under the curve (AUC) of nomogram for predicting 6-month PFS reached 0.847 (0.737-0.957), 0.786 (0.566-1.000) and 0.864 (0.735-0.994) in the training set, validation set and testing set, respectively. The AUC of nomogram for predicting 1-year OS reached 0.770 (0.635-0.906), 0.743 (0.479-1.000) and 0.818 (0.630-1.000), respectively. The AUC of nomogram for predicting ORR reached 0.914 (0.828-1.00), 0.938 (0.840-1.00) and 0.846 (0.689-1.00), respectively.

CONCLUSION

The prognostic models based on MR imaging features and clinical data are effective in predicting the PFS, OS and ORR of chemoimmunotherapy in pancreatic cancer patients with hepatic metastasis, and can be used to evaluate the prognosis of patients.

The association between gout flares and monosodium urate burden assessed using musculoskeletal ultrasound in patients with gout

Background

Ultrasound (US) has a high sensitivity in detecting monosodium urate (MSU) deposition in gout patients. However, the value of US in predicting gout flares has been reported only in a few monocentric studies.

Objective

To investigate the association between gout flares in the previous year and US-detected MSU burden using two different US scores.

Design

A retrospective study.

Methods

Patients with gout were consecutively recruited to undergo musculoskeletal US examinations of their knees, ankles, and feet. The score derived from Outcome Measure in Rheumatology (hereinafter referred to as MSU score) and musculoskeletal US features-based (hereinafter referred to as MSKF score) were used to quantify the MSU burden of gout. Odds ratios for frequent gout flares were calculated.

Results

We enrolled 1894 patients with gout (mean age: 45 years; gout duration: 5 years; males: 96.1%), experiencing a median of three flares over the past year. Of these, 428 (22.6%) patients reported frequent (⩾7) gout flares. The MSU and MSKF median scores were 6 and 9, respectively. For each five-point increase in MSU and MSKF score, the odds ratio of frequent gout flares increased 1.13-fold and 1.24-fold, respectively. The area under the curve (AUC) for the MSU and MSKF score was 0.635 [95% confidence interval (CI): 0.604-0.665] and 0.688 (95% CI: 0.659-0.718), respectively, (AUC difference 0.054, p value for AUC difference < 0.001).

Conclusion

The MSU and MSKF scores were significantly associated with the number of gout flares in the previous year. The MSKF score outperformed the MSU score in terms of frequent gout flare discrimination.

Endothelium-specific SIRT7 targeting ameliorates pulmonary hypertension through Krüpple-like factor 4 deacetylation

AIMS

Pulmonary hypertension (PH) is a pulmonary vascular disease characterized by a high mortality rate. Pulmonary arterial endothelium cells (PAECs) serve as a primary sensor of various environmental cues, such as shear stress and hypoxia, but PAEC dysfunction may trigger vascular remodelling during the onset of PH. This study aimed to illustrate the role of Sirtuin 7 (SIRT7) in endothelial dysfunction during PH and explore the potential therapeutic strategy for PH.

METHODS AND RESULTS

SIRT7 levels were measured in human and murine experimental PH samples. Bioinformatic analysis, immunoprecipitation, and deacetylation assay were used to identify the association between SIRT7 and Krüpple-like factor 4 (KLF4), a key transcription factor essential for endothelial cell (EC) homeostasis. Sugen5416 + hypoxia (SuHx)-induced PH mouse models and cell cultures were used for the study of the therapeutic effect of SIRT7 for PH. SIRT7 level was significantly reduced in lung tissues and PAECs from PH patients and the SuHx-induced PH mouse model as compared with healthy controls. Pulmonary endothelium-specific depletion of Sirt7 increased right ventricular systolic pressure and exacerbated right ventricular hypertrophy in the SuHx-induced PH model. At the molecular level, we identified KLF4 as a downstream target of SIRT7, which deacetylated KLF4 at K228 and inhibited the ubiquitination-proteasome degradation. Thus, the SIRT7/KLF4 axis maintained PAEC homeostasis by regulating proliferation, migration, and tube formation. PAEC dysfunction was reversed by adeno-associated virus type 1 vector-mediated endothelial overexpression of Sirt7 or supplementation with nicotinamide adenine dinucleotide (NAD)+ intermediate nicotinamide riboside which activated Sirt7; both approaches successfully reversed PH phenotypes.

CONCLUSION

The SIRT7/KLF4 axis ensures PAEC homeostasis, and pulmonary endothelium-specific SIRT7 targeting might constitute a PH therapeutic strategy.

Mitogen-activated protein kinases MPK3 and MPK6 phosphorylate receptor-like cytoplasmic kinase CDL1 to regulate soybean basal immunity

Soybean cyst nematode (SCN; Heterodera glycines Ichinohe), one of the most devastating soybean (Glycine max) pathogens, causes significant yield loss in soybean production. Nematode infection triggers plant defense responses; however, the components involved in the upstream signaling cascade remain largely unknown. In this study, we established that a mitogen-activated protein kinase (MAPK) signaling module, activated by nematode infection or wounding, is crucial for soybeans to establish SCN resistance. GmMPK3 and GmMPK6 directly interact with CDG1-LIKE1 (GmCDL1), a member of the receptor-like cytoplasmic kinase (RLCK) subfamily VII. These kinases phosphorylate GmCDL1 at Thr-372 to prevent its proteasome-mediated degradation. Functional analysis demonstrated that GmCDL1 positively regulates immune responses and promotes SCN resistance in soybeans. GmMPK3-mediated and GmMPK6-mediated phosphorylation of GmCDL1 enhances GmMPK3 and GmMPK6 activation and soybean disease resistance, representing a positive feedback mechanism. Additionally, 2 L-type lectin receptor kinases, GmLecRK02g and GmLecRK08g, associate with GmCDL1 to initiate downstream immune signaling. Notably, our study also unveils the potential involvement of GmLecRKs and GmCDL1 in countering other soybean pathogens beyond nematodes. Taken together, our findings reveal the pivotal role of the GmLecRKs-GmCDL1-MAPK regulatory module in triggering soybean basal immune responses.

Prognostic difference between surgery and external radiation in patients with stage I liver cancer based on competitive risk model and conditional survival rate

PURPOSE

This study aimed to assess the difference in prognosis of patients with early-stage liver cancer after surgery or external radiation.

METHODS

Between 2010 and 2015, 2155 patients with AJCC 7th stage I liver cancer were enrolled in the SEER database. Among these, 1972 patients had undergone surgery and 183 had undergone external beam radiation. The main research endpoints were overall survival (OS) and disease-specific survival (DSS). The competitive risk model was used to calculate the risk ratio of liver cancer-specific deaths when there was a competitive risk. Propensity Score Matching (PSM) method using a 1:1 ratio was used to match confounders such as sex, age, and treatment method. Conditional survival was dynamically assessed for patient survival after surgery or external radiation.

RESULTS

Multivariate analysis of the competitive risk model showed that age, disease diagnosis time, grade, and treatment [surgery and external beam radiation therapy (EBRT)] were independent prognostic factors for patients with hepatocellular carcinoma. Surgery had a higher survival improvement rate than that of EBRT. As the survival of patients with liver cancer increased, the survival curve of surgery declined more slowly than that of radiotherapy patients and stabilized around 3 years after surgery. The survival curve of radiotherapy patients significantly dropped within 4 years and then stabilized.

CONCLUSION

Surgery was better than EBRT for patients with stage I liver cancer. Close follow-up was required for 3 years after surgery or 4 years after external radiation. This study can help clinicians make better informed clinical decisions.

Characterization of the complete mitochondrial genome of Desmaulus extinctorium (Littorinimorpha, Calyptraeoidea, Calyptraeidae) and molecular phylogeny of Littorinimorpha

For the purpose of determining the placement of Calyptraeidae within the Littorinimorpha, we hereby furnish a thorough analysis of the mitochondrial genome (mitogenome) sequence of Desmaulus extinctorium. This mitogenome spans 16,605 base pairs and encompasses the entire set of 37 genes, including 13 PCGs, 22 tRNAs and two rRNAs, with an evident AT bias. Notably, tRNASer1 and tRNASer2 lack dihydrouracil (DHU) arms, resulting in an inability to form a secondary structure. Similarly, tRNAAla lacks a TΨC arm, rendering it incapable of forming a secondary structure. In contrast, the remaining tRNAs demonstrate a characteristic secondary structure reminiscent of a cloverleaf. A comparison with ancestral gastropods reveals distinct differences in three gene clusters (or genes), encompassing 15 tRNAs and eight PCGs. Notably, inversions and translocations represent the major types of rearrangements observed in D. extinctorium. Phylogenetic analysis demonstrates robust support for a monophyletic grouping of all Littorinimorpha species, with D. extinctorium representing a distinct Calyptraeoidea clade. In summary, this investigation provides the first complete mitochondrial dataset for a species of the Calyptraeidae, thus providing novel insights into the phylogenetic relationships within the Littorinimorpha.

MUSCLE: multi-view and multi-scale attentional feature fusion for microRNA-disease associations prediction

MicroRNAs (miRNAs) synergize with various biomolecules in human cells resulting in diverse functions in regulating a wide range of biological processes. Predicting potential disease-associated miRNAs as valuable biomarkers contributes to the treatment of human diseases. However, few previous methods take a holistic perspective and only concentrate on isolated miRNA and disease objects, thereby ignoring that human cells are responsible for multiple relationships. In this work, we first constructed a multi-view graph based on the relationships between miRNAs and various biomolecules, and then utilized graph attention neural network to learn the graph topology features of miRNAs and diseases for each view. Next, we added an attention mechanism again, and developed a multi-scale feature fusion module, aiming to determine the optimal fusion results for the multi-view topology features of miRNAs and diseases. In addition, the prior attribute knowledge of miRNAs and diseases was simultaneously added to achieve better prediction results and solve the cold start problem. Finally, the learned miRNA and disease representations were then concatenated and fed into a multi-layer perceptron for end-to-end training and predicting potential miRNA-disease associations. To assess the efficacy of our model (called MUSCLE), we performed 5- and 10-fold cross-validation (CV), which got average the Area under ROC curves of 0.966${\pm }$0.0102 and 0.973${\pm }$0.0135, respectively, outperforming most current state-of-the-art models. We then examined the impact of crucial parameters on prediction performance and performed ablation experiments on the feature combination and model architecture. Furthermore, the case studies about colon cancer, lung cancer and breast cancer also fully demonstrate the good inductive capability of MUSCLE. Our data and code are free available at a public GitHub repository: https://github.com/zht-code/MUSCLE.git.

MGCNSS: miRNA-disease association prediction with multi-layer graph convolution and distance-based negative sample selection strategy

Identifying disease-associated microRNAs (miRNAs) could help understand the deep mechanism of diseases, which promotes the development of new medicine. Recently, network-based approaches have been widely proposed for inferring the potential associations between miRNAs and diseases. However, these approaches ignore the importance of different relations in meta-paths when learning the embeddings of miRNAs and diseases. Besides, they pay little attention to screening out reliable negative samples which is crucial for improving the prediction accuracy. In this study, we propose a novel approach named MGCNSS with the multi-layer graph convolution and high-quality negative sample selection strategy. Specifically, MGCNSS first constructs a comprehensive heterogeneous network by integrating miRNA and disease similarity networks coupled with their known association relationships. Then, we employ the multi-layer graph convolution to automatically capture the meta-path relations with different lengths in the heterogeneous network and learn the discriminative representations of miRNAs and diseases. After that, MGCNSS establishes a highly reliable negative sample set from the unlabeled sample set with the negative distance-based sample selection strategy. Finally, we train MGCNSS under an unsupervised learning manner and predict the potential associations between miRNAs and diseases. The experimental results fully demonstrate that MGCNSS outperforms all baseline methods on both balanced and imbalanced datasets. More importantly, we conduct case studies on colon neoplasms and esophageal neoplasms, further confirming the ability of MGCNSS to detect potential candidate miRNAs. The source code is publicly available on GitHub https://github.com/15136943622/MGCNSS/tree/master.

A Review of Dupilumab in the Treatment of Atopic Dermatitis in Infants and Children

Atopic dermatitis (AD), a common pruritic and chronic inflammatory skin disease, has a major impact on a patient's quality of life. It is characterized by dry, itchy, and eczema-like rashes. AD is more prevalent in young children and has been linked to a variety of other allergy disorders. Traditional drug therapy has certain limitations for treating young children with AD. However, biologics have good clinical application prospects in the medical treatment of young patients. Dupilumab, a fully human monoclonal antibody, specifically binds to the IL-4 Rα subunit, inhibiting IL-4 and IL-13 signaling and blocking the occurrence of type 2 inflammatory response. It has a good effect on treating infants and children with moderate-to-severe AD. This review explores the safety and efficacy of dupilumab in the treatment of AD in infants and children and the impact of early intervention on AD progression, with the aim of informing clinical practice in the use of dupilumab for the treatment of young patients with AD.

A new paradigm for applying deep learning to protein-ligand interaction prediction

Protein-ligand interaction prediction presents a significant challenge in drug design. Numerous machine learning and deep learning (DL) models have been developed to accurately identify docking poses of ligands and active compounds against specific targets. However, current models often suffer from inadequate accuracy or lack practical physical significance in their scoring systems. In this research paper, we introduce IGModel, a novel approach that utilizes the geometric information of protein-ligand complexes as input for predicting the root mean square deviation of docking poses and the binding strength (pKd, the negative value of the logarithm of binding affinity) within the same prediction framework. This ensures that the output scores carry intuitive meaning. We extensively evaluate the performance of IGModel on various docking power test sets, including the CASF-2016 benchmark, PDBbind-CrossDocked-Core and DISCO set, consistently achieving state-of-the-art accuracies. Furthermore, we assess IGModel's generalizability and robustness by evaluating it on unbiased test sets and sets containing target structures generated by AlphaFold2. The exceptional performance of IGModel on these sets demonstrates its efficacy. Additionally, we visualize the latent space of protein-ligand interactions encoded by IGModel and conduct interpretability analysis, providing valuable insights. This study presents a novel framework for DL-based prediction of protein-ligand interactions, contributing to the advancement of this field. The IGModel is available at GitHub repository https://github.com/zchwang/IGModel.