Early application of metagenomics next-generation sequencing may significantly reduce unnecessary consumption of antibiotics in patients with fever of unknown origin.

BACKGROUND: Metagenomic next-generation sequencing (mNGS) is a novel nucleic acid method for the detection of unknown and difficult pathogenic microorganisms, and its application in the etiological diagnosis of fever of unknown origin (FUO) is less reported. We aimed to comprehensively assess the value of mNGS in the etiologic diagnosis of FUO by the pathogen spectrum and diagnostic performance, and to investigate whether it is different in the time to diagnosis, length of hospitalization, antibiotic consumption and cost between FUO patients with and without early application of mNGS. METHODS: A total of 149 FUO inpatients underwent both mNGS and routine pathogen detection was retrospectively analyzed. The diagnostic performance of mNGS, culture and CMTs for the final clinical diagnosis was evaluated by using sensitivity, specificity, positive predictive value, negative predictive value and total conforming rate. Patients were furtherly divided into two groups: the earlier mNGS detection group (sampling time: 0 to 3 days of the admission) and the later mNGS detection group (sampling time: after 3 days of the admission). The length of hospital stay, time spent on diagnosis, cost and consumption of antibiotics were compared between the two groups. RESULTS: Compared with the conventional microbiological methods, mNGS detected much more species and had the higher negative predictive (67.6%) and total conforming rate (65.1%). Patients with mNGS sampled earlier had a significantly shorter time to diagnosis (6.05+/-6.23 vs. 10.5+/-6.4 days, P < 0.001) and days of hospital stay (13.7+/-20.0 vs. 30.3 +/-26.9, P < 0.001), as well as a significantly less consumption (13.3+/-7.8 vs. 19.5+/-8.0, P < 0.001) and cost (4543+/-7326 vs. 9873 +/- 9958 China Yuan [CNY], P = 0.001) of antibiotics compared with the patients sampled later. CONCLUSIONS: mNGS could significantly improve the detected pathogen spectrum, clinical conforming rate of pathogens while having good negative predictive value for ruling out infections. Early mNGS detection may shorten the diagnosis time and hospitalization days and reduce unnecessary consumption of antibiotics.

A case report of brainstem hemorrhage due to Rhizopus delemar-induced encephalitis diagnosed by metagenomic next-generation sequencing (mNGS).

BACKGROUND: Rhizopus delemar is an invasive fungal pathogen that can cause fatal mucormycosis in immunodeficient individuals. Encephalitis caused by R. delemar is rare and difficult to diagnose early. Clinical detection methods for R. delemar include blood fungal culture, direct microscopic examination, and histopathological examination, but the detection is often inadequate for clinical diagnosis and can easily lead to missed diagnosis with delayed treatment. CASE PRESENTATION: We report a case of a 47-year-old male with brainstem hemorrhage caused by encephalitis due to R. delemar. The patient had a history of hypertension, type 2 diabetes, and irregular medication. No pathogens were detected in cerebrospinal fluid (CSF) and nasopharyngeal secretion cultures. R. delemar was identified by metagenomic next-generation sequencing (mNGS) in CSF, and in combination with the patient's clinical characteristics, encephalitis caused by R. delemar was diagnosed. Antibiotic treatment using amphotericin B liposome in combination with posaconazole was given immediately. However, due to progressive aggravation of the patient's symptoms, he later died due to brainstem hemorrhage after giving up treatment. CONCLUSIONS: mNGS technique is a potential approach for the early diagnosis of infections, which can help clinicians provide appropriate antibiotic treatments, thus reducing the mortality and disability rate of patients.

Resource allocation strategies among vegetative growth, sexual reproduction, asexual reproduction and defense during growing season of Aconitum kusnezoffii Reichb.

Natural plants must actively allocate their limited resources for survival and reproduction. Although vegetative growth, sexual reproduction, asexual reproduction and defense are all basic processes in the life cycle of plants, the strategies used to allocate resources between these processes are poorly understood. These processes are conspicuous in naturally grown Aconitum kusnezoffii Reichb., which makes it a suitable study subject. Here, the morphology, dry matter, total organic carbon, total nitrogen and aconitum alkaloid levels of shoot, principal root (PR) and lateral roots were measured throughout the growing season. Then, transcriptome and metabolite content analyses were performed. We found that vegetative growth began first. After vegetative growth ceased, sexual development began. Flower organ development was accompanied by increased photosynthesis and the PR consumed temporarily stored resources after flower formation. Asexual propagule development initiated earlier than sexual reproduction and kept accumulating resources after that. Development was slow before flower formation, mainly manifesting as increasing length; then, after flower formation it accelerated via enhanced material transport and accumulation. Defense compounds were maintained at low levels before flowering. In particular, the turnover of defense compounds was enhanced before and after flower bud emergence, providing resources for other processes. After flower formation, defense compounds were accumulated. The pattern found herein provides a vivid example for further studies on resource allocation strategies. The exciting finding that the PR, as a more direct storage site for photosynthate, is a buffer unit for resources, and that defense compounds can be reused for other processes, suggests a need to explore potential mechanisms.

Concurrent infection of Exophiala dermatitidis and Angiostrongylus cantonensis in central nervous system of a child with inherited CARD9 deficiency: A case report and literature review.

Exophiala dermatitidis is a relatively common environmental black yeast with a worldwide distribution that rarely causes fungal infection. Here, we report a case of a 6-year-old girl with central nervous system (CNS) encephalitis caused by E. dermatitidis and Angiostrongylus cantonensis. E. dermatitidis was identified by both cerebrospinal fluid culture and metagenomic next-generation sequencing (mNGS). Angiostrongylus cantonensis infection was confirmed by an enzyme linked immunosorbent assay (ELISA). Whole exome sequencing showed that this previously healthy girl carried a homozygous CARD9 mutation for c.820dupG (p.D274Gfs*61) that underlies invasive fungal and parasite infections. We chose glucocortieoid pulse therapy and anti-infective therapy based on the initial results of laboratory examination and cranial MRI images. With the aggravation of the disease and the evidence of the subsequent etiologic test, the combination of antifungal antiparasitic treatments (voriconazole, fluorocytosine and amphotericin B) were actively used. Unfortunately, the girl finally died due to severe systemic infection. mNGS performs a potential value for diagnosing rare CNS infections, and autosomal recessive CARD9 deficiency should be considered in patient with fatal invasive fungal infections.

Breaking boundaries in radiology: redefining AI diagnostics via raw data ahead of reconstruction.

Objective.In the realm of utilizing artificial intelligence (AI) for medical image analysis, the paradigm of 'signal-image-knowledge' has remained unchanged. However, the process of 'signal to image' inevitably introduces information distortion, ultimately leading to irrecoverable biases in the 'image to knowledge' process. Our goal is to skip reconstruction and build a diagnostic model directly from the raw data (signal).Approach. This study focuses on computed tomography (CT) and its raw data (sinogram) as the research subjects. We simulate the real-world process of 'human-signal-image' using the workflow 'CT-simulated data- reconstructed CT,' and we develop a novel AI predictive model directly targeting raw data (RCTM). This model comprises orientation, spatial, and global analysis modules, embodying the fusion of local to global information extraction from raw data. We selected 1994 patients with retrospective cases of solid lung nodules and modeled different types of data.Main results. We employed predefined radiomic features to assess the diagnostic feature differences caused by reconstruction. The results indicated that approximately 14% of the features had Spearman correlation coefficients below 0.8. These findings suggest that despite the increasing maturity of CT reconstruction algorithms, they still introduce perturbations to diagnostic features. Moreover, our proposed RCTM achieved an area under the curve (AUC) of 0.863 in the diagnosis task, showcasing a comprehensive superiority over models constructed from secondary reconstructed CTs (0.840, 0.822, and 0.825). Additionally, the performance of RCTM closely resembled that of models constructed from original CT scans (0.868, 0.878, and 0.866).Significance. The diagnostic and therapeutic approach directly based on CT raw data can enhance the precision of AI models and the concept of 'signal-to-image' can be extended to other types of imaging. AI diagnostic models tailored to raw data offer the potential to disrupt the traditional paradigm of 'signal-image-knowledge', opening up new avenues for more accurate medical diagnostics.

Integrating Radiomics and Neural Networks for Knee Osteoarthritis Incidence Prediction.

OBJECTIVE: Accurately predicting knee osteoarthritis (KOA) is essential for early detection and personalized treatment. We aimed to develop and test a magnetic resonance imaging (MRI)-based joint space (JS) radiomic model (RM) to predict radiographic KOA incidence through neural networks by integrating meniscus and femorotibial cartilage radiomic features. METHODS: In the Osteoarthritis Initiative cohort, participants with knees without radiographic KOA at baseline but at high risk for radiographic KOA were included. Patients' knees developed radiographic KOA, whereas control knees did not over four years. We randomly split the participants into development and test cohorts (8:2) and extracted features from baseline three-dimensional double-echo steady-state sequence MRI. Model performance was evaluated using an area under the receiver operating characteristic curve (AUC), sensitivity, and specificity in both cohorts. Nine resident surgeons performed the reader experiment without/with the JS-RM aid. RESULTS: Our study included 549 knees in the development cohort (275 knees of patients with KOA vs 274 knees of controls) and 137 knees in the test cohort (68 knees of patients with KOA vs 69 knees of controls). In the test cohort, JS-RM had a favorable accuracy for predicting the radiographic KOA incidence with an AUC of 0.931 (95% confidence interval [CI] 0.876-0.963), a sensitivity of 84.4% (95% CI 83.9%-84.9%), and a specificity of 85.6% (95% CI 85.2%-86.0%). The mean specificity and sensitivity of resident surgeons through MRI reading in predicting radiographic KOA incidence were increased from 0.474 (95% CI 0.333-0.614) and 0.586 (95% CI 0.429-0.743) without the assistance of JS-RM to 0.874 (95% CI 0.847-0.901) and 0.812 (95% CI 0.742-0.881) with JS-RM assistance, respectively (P < 0.001). CONCLUSION: JS-RM integrating the features of the meniscus and cartilage showed improved predictive values in radiographic KOA incidence.

Identification of a metagenome-derived prephenate dehydrogenase gene from an alkaline-polluted soil microorganism.

A novel prephenate dehydrogenase gene designated pdhE-1 was cloned by sequence-based screening of a plasmid metagenomic library from uncultured alkaline-polluted microorganisms. The deduced amino acid sequence comparison and phylogenetic analysis indicated that PdhE-1 and other putative prephenate dehydrogenases were closely related. The putative prephenate dehydrogenase gene was subcloned into pETBlue-2 vector and overexpressed in Escherichia coli BL21(DE3) pLacI. The recombinant protein was purified to homogeneity. The maximum activity of the PdhE-1 protein occurred at pH 8.0 and 45 °C using prephenic acid as the substrate. The prephenate dehydrogenase had an apparent K m value of 0.87 mM, a V max value of 41.5 U/mg, a k cat value of 604.8/min and a k cat/K m value of 1.16 × 10(4)/mol/s. L-Tyrosine did not obviously inhibit the recombinant PdhE-1 protein. The identification of a metagnome-derived prephenate dehydrogenase provides novel material for studies and application of proteins involved in tyrosine biosynthesis.

Antinociceptive effects of cefadroxil and ceftriaxone in experimental animal models of pain.

BACKGROUND: As an "off-target" effect, cephalosporins can enhance glutamate transporter-1 expression in astrocytes to recycle glutamate from synaptic cleft, and exhibited analgesic properties in animals and humans with chronic pain. METHODS: In the present study, we focused on making a side-by-side comparison of the analgesic potentials of cefadroxil and ceftriaxone, using rodent models of peripheral neuropathic pain, inflammatory pain and incisional pain. Microdialysis technique was adopted to validate the in vivo glutamate regulatory properties of these two drugs in central nervous system. RESULTS: We have shown that cefadroxil and ceftriaxone are beneficial in a variety of pain scenarios, without inducing observable side effects. The two cephalosporins worked better on neuropathic pain, rather than inflammatory pain or incisional pain, suggesting nociceptive system was differentially affected. Further, microdialysis has confirmed that cephalosporins can effectively reverse the elevated levels of glutamate in brain of animals with neuropathic pain. CONCLUSIONS: The outcome of this study may guide us to identify a molecular skeleton derived from cefadroxil, based on which we could possibly develop new non-antibiotic analgesic compounds with glutamate recycling properties.

The common neurological basis and targeted therapeutic approaches for chronic pain and opioid addiction.

Chronic pain and drug addiction seriously threaten human health and generate a large loss of labor. Most highly addictive drugs are derived from opioids, which have severe side effects and are difficult to quit completely. On the other hand, opioid analgesics are widely used in detoxification for opioid addiction. These opioids are effective for controlling acute withdrawal symptoms, but can be problematic under long-term usage as maintenance therapy. Both chronic pain and opioid abuse are related to neurotransmitters and central reward pathways in the brain. As to provide new weapons for defending human health, this article summarized the similarities and differences between chronic pain and opioid addiction, based on their common neurobiological basis, and discussed the breakthroughs in targeted therapeutic approaches. Furthermore, we have brought out an innovative and integrative therapeutic scheme by combining drugs, medical devices, and phycological / behavioral therapies, according to the patient's individual situation, aiming at achieving better effects against these two types of diseases.

Screening of potential microbial markers for lung cancer using metagenomic sequencing.

INTRODUCTION: Lung cancer is the most prevalent cancer with high mortality in China, and it is associated with the dysbiosis of the lung microbiome. This study attempted to screen for specific microorganisms as potential biomarkers for distinguishing benign lung disease from lung cancer. METHODS: Bronchoalveolar lavage fluid (BALF) sample was selected in the study instead of saliva to avoid contamination with oral microorganisms, and microbial taxonomic and functional differences in BALF samples from patients with lung cancer and those with those from patients with benign lung diseases were performed based on metagenomic next-generation sequencing, for the first time, so that microorganisms other than bacteria could be included. RESULTS: The results showed that the intrasample diversity of malignant samples was different from benign samples, and the microbial differences among malignant samples were smaller, with lower microbial diversity, significantly changed microbial abundance and metabolic functions. Metabolic function analysis revealed amino acid-related metabolism was more prevalent in benign samples, whereas carbohydrate-related metabolism was more prevalent in malignant samples. By LEfSe, Metastat and Random Forest analysis, we identified a series of important differential microorganisms. Importantly, the model combining five key genera plus one tumor marker (neuron-specific enolase) as indicators presented the optimal disease typing performance. CONCLUSION: Thus results suggest the value of these differential microorganisms enriched in tumors in mechanism research and may be potential new targets for lung cancer therapy. More importantly, the biomarkers identified in this study can be conducive to improve the clinical diagnosis of lung cancer and have good application prospects.

Microbiota-derived short-chain fatty acids mediate the effects of dengzhan shengmai in ameliorating cerebral ischemia via the gut-brain axis.

ETHNOPHARMACOLOGICAL RELEVANCE: Dengzhan shengmai (DZSM) formula, composed of four herbal medicines (Erigeron breviscapus, Panax ginseng, Schisandra chinensis, and Ophiopogon japonicus), is widely used in the recovery period of ischemic cerebrovascular diseases; however, the associated molecular mechanism remains unclear. AIM OF THE STUDY: The purpose of this study was to uncover the links between the microbiota-gut-brain axis and the efficacy of DZSM in ameliorating cerebral ischemic diseases. MATERIALS AND METHODS: The effects of DZSM on the gut microbiota community and bacteria-derived short-chain fatty acid (SCFA) production were evaluated in vivo using a rat model of cerebral ischemia and in vitro through the anaerobic incubation with fresh feces derived from model animals. Subsequently, the mechanism underlying the role of SCFAs in the DZSM-mediated treatment of cerebral ischemia was explored. RESULTS: We found that DZSM treatment significantly altered the composition of the gut microbiota and markedly enhanced SCFA production. The consequent increase in SCFA levels led to the upregulation of the expression of monocarboxylate transporters and facilitated the transportation of intestinal SCFAs into the brain, thereby inhibiting the apoptosis of neurocytes via the regulation of the PI3K/AKT/caspase-3 pathway. The increased intestinal SCFA levels also contributed to the repair of the 2VO-induced disruption of gut barrier integrity and inhibited the translocation of lipopolysaccharide from the intestine to the brain, thus attenuating neuroinflammation. Consequently, cerebral neuropathy and oxidative stress were significantly improved in 2VO model rats, leading to the amelioration of cerebral ischemia-induced cognitive dysfunction. Finally, fecal microbiota transplantation could reproduce the beneficial effects of DZSM on SCFA production and cerebral ischemia. CONCLUSIONS: Our findings suggested that SCFAs mediate the effects of DZSM in ameliorating cerebral ischemia via the gut microbiota-gut-brain axis.

Enhancing urinary tract infection diagnosis for negative culture patients with metagenomic next-generation sequencing (mNGS).

Background: Metagenomic next-generation sequencing (mNGS) is a promising technology that allows unbiased pathogen detection and is increasingly being used for clinical diagnoses. However, its application in urinary tract infection (UTI) is still scarce. Methods: The medical records of 33 patients with suspected UTI who were admitted to the Second Hospital of Tianjin Medical University from March 2021 to July 2022 and received urine mNGS were retrospectively analyzed. The performance of mNGS and conventional urine culture in diagnosing infection and identifying causative organisms was compared, and the treatment effects were evaluated in terms of changes in urinalyses and urinary symptoms. Results: In the detection of bacteria and fungi, mNGS detected at least one pathogen in 29 (87.9%) cases, including 19 (57.6%) with positive mNGS but negative culture results and 10 (30.3%) with both mNGS and culture positive results. The remaining 4 (12.1%) patients were negative by both tests. Overall, mNGS performed better than culture (87.9% vs. 30.3%, P < 0.001). Within the 10 double-positive patients, mNGS matched culture results exactly in 5 cases, partially in 4 cases, and not at all in 1 case. In addition, mNGS detected a broader pathogen spectrum, detecting 26 species compared to only 5 species found in culture. The most abundant bacteria detected by mNGS was Escherichia coli, detected in 9 (27.2%) patients. All anaerobic bacteria, Mycobacterium Tuberculosis and all mixed pathogens were detected by mNGS. The final clinical diagnosis of UTI was made in 25 cases, and the sensitivity of mNGS was significantly higher than culture (100.0% vs 40.0%; P < 0.001) when using the diagnosis as a reference standard; the positive predictive value, negative predictive value and specificity were 86.2%, 100% and 50.0%, respectively. Importantly, targeted antibiotic therapy based on mNGS resulted in significant improvement in urinalyses and urinary symptoms in patients. Conclusions: mNGS is a technology that has shown clear advantages over culture, particularly in the context of mixed infections and UTIs that are difficult to diagnose and treat. It helps to improve the detection of pathogens, guide changes in treatment strategies, and is an effective complement to urine culture.

Analgesic Alkaloids Derived From Traditional Chinese Medicine in Pain Management.

Chronic pain is one of the most prevalent health problems. The establishment of chronic pain is complex. Current medication for chronic pain mainly dependent on anticonvulsants, tricyclic antidepressants and opioidergic drugs. However, they have limited therapeutic efficacy, and some even with severe side effects. We turned our interest into alkaloids separated from traditional Chinese medicine (TCM), that usually act on multiple drug targets. In this article, we introduced the best-studied analgesic alkaloids derived from TCM, including tetrahydropalmatine, aloperine, oxysophocarpine, matrine, sinomenine, ligustrazine, evodiamine, brucine, tetrandrine, Stopholidine, and lappaconitine, focusing on their mechanisms and potential clinical applications. To better describe the mechanism of these alkaloids, we adopted the concept of drug-cloud (dCloud) theory. dCloud illustrated the full therapeutic spectrum of multitarget analgesics with two dimensions, which are "direct efficacy", including inhibition of ion channels, activating γ-Aminobutyric Acid/opioid receptors, to suppress pain signal directly; and "background efficacy", including reducing neuronal inflammation/oxidative stress, inhibition of glial cell activation, restoring the balance between excitatory and inhibitory neurotransmission, to cure the root causes of chronic pain. Empirical evidence showed drug combination is beneficial to 30-50% chronic pain patients. To promote the discovery of effective analgesic combinations, we introduced an ancient Chinese therapeutic regimen that combines herbal drugs with "Jun", "Chen", "Zuo", and "Shi" properties. In dCloud, "Jun" drug acts directly on the major symptom of the disease; "Chen" drug generates major background effects; "Zuo" drug has salutary and supportive functions; and "Shi" drug facilitates drug delivery to the targeted tissue. Subsequently, using this concept, we interpreted the therapeutic effect of established analgesic compositions containing TCM derived analgesic alkaloids, which may contribute to the establishment of an alternative drug discovery model.

Elevational is the main factor controlling the soil microbial community structure in alpine tundra of the Changbai Mountain.

To reveal the self-coordination mechanism of the fragile ecosystem of alpine tundra, we explored the relationship between soil microorganisms and other elements. On the alpine tundra of the Changbai Mountain, different vegetation types, altitudes and soil properties were selected as driving factors of soil microbial community. Soil microbial community, C- and N-cycling functional microbial and fungal biomass were analyzed. Structural equation model was used to study the control of biotic and abiotic factors in rhizosphere soil microbial community. The results showed that the pH value of soil had the strongest direct impact on the diversity and community structure of soil microorganisms, and had significant correlation with most of the C- and N-cycling functional microbial; organic carbon and vegetation also have strongest direct effect on fungal biomass, but all of them were not main factors influence soil microbial community structure, the elevation was the main controlling factor. In addition, the elevation mainly through indirect action affects the soil microbial community by driving distribution of plant species, soil organic carbon and pH value. This finding highlighted that elevation was the main predictor to determine rhizosphere microbial community structure but not vegetation in alpine tundra of Changbai Mountain.

Site-specific, covalent immobilization of an engineered enterokinase onto magnetic nanoparticles through transglutaminase-catalyzed bioconjugation.

Enterokinase (EK) is one of the most popular enzymes for the in vitro cleavage of fusion proteins due to its high degree of specificity for the amino-acid sequence (Asp)4-Lys. Enzyme reusability is desirable for reducing operating costs and facilitating the industrial application of EK. In this work, we report the controlled, site-specific and covalent cross-linking of an engineered EKLC on amine-modified magnetic nanoparticles (NH2-MNPs) via microbial transglutaminase-catalyzed bioconjugation for the development of the oriented-immobilized enzyme, namely, EKLC@NH2-MNP biocatalyst. Upon the site-specific immobilization, approximately 90% EKLC enzymatic activity was retained, and the biocatalyst exhibited more than 85% of initial enzymatic activity regardless of storage or reusable stability over a month. The EKLC@NH2-MNP biocatalyst was further applied to remove the His tag-(Asp)4-Lys fusion partner from the His tag-(Asp)4-Lys-(GLP-1)3 substrate fusion protein, result suggested the EKLC@NH2-MNP possessed remarkable reusability, without a significant decrease of enzymatic activity over 10 cycles (P > 0.05). Supported by the unique properties of MNPs, the proposed EKLC@NH2-MNP biocatalyst is expected to promote the economical utilization of enterokinase in fusion protein cleavage.