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Abstract Background and objective Community-acquired pneumonia (CAP) is a common respiratory disease that frequently requires hospitalisation, and is a significant cause of death worldwide. This study aimed to evaluate the usefulness of alpha-1-antichymotrypsin (AACT) as a diagnostic and prognostic biomarker of CAP. Methods We conducted a multicentre prospective cohort study in patients hospitalised with CAP. Plasma AACT levels were measured using a quantitative enzyme-linked immunosorbent assay. Receiver-operating characteristic (ROC) curves and Cox proportional hazards regression were used to assess the association between plasma AACT levels and CAP diagnosis and prognosis. Results A total of 274 patients with CAP were enrolled in the study. AACT levels were elevated in patients with CAP, especially those with severe CAP and non-survivors. The area under the curve (AUC) of AACT and CRP for diagnosing CAP was 0.755 and 0.843. Cox regression showed that CURB-65 and AACT levels were independent predictors of 30-day mortality. ROC curves showed that plasma AACT levels had the highest accuracy for predicting acute respiratory distress syndrome (ARDS), with an AUC of 0.862. Combining AACT with Pneumonia Severity Index and CURB-65 significantly improved their predictive accuracy for predicting 30-day mortality. Conclusion Plasma AACT levels are elevated in patients with CAP, but plasma AACT level is inferior to the C-reactive protein level for diagnosing CAP. The AACT level can reliably predict the occurrence of ARDS and 30-day mortality in patients with CAP.

Purpose Patients with bacterial, fungal, and viral community-acquired pneumonia (CAP) were studied to determine their metabolic profiles.Methods Loop-mediated isothermal amplification technology and nucleic acid sequence-dependent amplification combined with microfluidic chip technology were applied to screen multiple pathogens from respiratory tract samples. Eighteen patients with single bacterial infection (B-CAP), fifteen with single virus infection (V-CAP), twenty with single fungal infection (F-CAP), and twenty controls were enrolled. UHPLC-MS/MS analysis of untargeted serum samples for metabolic profiles. Multiple linear regression and Spearman’s rank correlation analysis were used to determine associations between metabolites and clinical parameters. The sensitivity and specificity of the screened metabolites were also examined, along with their area under the curve.Results The metabolic signatures of patients with CAP infected by bacteria, viruses, and fungi were markedly different from those of controls. The abundances of 45, 56, and 79 metabolites were significantly unbalanced. Among these differential metabolites, 11, 13, and 29 were unique to the B-CAP, V-CAP, and F-CAP groups, respectively. Bacterial infections were the only known causes of disturbances in the pentose and glucuronate and aldarate and ascorbate metabolism interconversions metabolic pathway.Conclusions Serum metabolomic techniques based on UHPLC-MS/MS may identify differences between individuals with CAP who have been infected by various pathogens, and they can also build a metabolite signature for early detection of the origin of infection and prompt care.

Since its initial release in 2001, the human reference genome has undergone continuous improvement in quality, and the recently released telomere-to-telomere (T2T) version — T2T-CHM13 — reaches its highest level of continuity and accuracy after 20 years of effort by working on a simplified, nearly homozygous genome of a hydatidiform mole cell line. Here, to provide an authentic complete diploid human genome reference for the Han Chinese, the largest population in the world, we assembled the genome of a male Han Chinese individual, T2T-YAO, which includes T2T assemblies of all the 22 + X + M and 22 + Y chromosomes in both haploids. The quality of T2T-YAO is much better than those of all currently available diploid assemblies, and its haploid version, T2T-YAO-hp, generated by selecting the better assembly for each autosome, reaches the top quality of fewer than one error per 29.5 Mb, even higher than that of T2T-CHM13. Derived from an individual living in the aboriginal region of the Han population, T2T-YAO shows clear ancestry and potential genetic continuity from the ancient ancestors. Each haplotype of T2T-YAO possesses ∼ 330-Mb exclusive sequences, ∼ 3100 unique genes, and tens of thousands of nucleotide and structural variations as compared with CHM13, highlighting the necessity of a population-stratified reference genome. The construction of T2T-YAO, an accurate and authentic representative of the Chinese population, would enable precise delineation of genomic variations and advance our understandings in the hereditability of diseases and phenotypes, especially within the context of the unique variations of the Chinese population.

BackgroundTo date, more than 770 million individuals have become coronavirus disease 2019 (COVID-19) convalescents worldwide. Emerging evidence highlights the influence of COVID-19 on the oral microbiome during both acute and convalescent disease phases. Front-line healthcare workers are at an elevated risk of exposure to viral infections, and the effects of COVID-19 on their oral microbiome remain relatively unexplored.MethodsOropharyngeal swab specimens, collected one month after a negative COVID-19 test from a cohort comprising 55 healthcare workers, underwent 16S rRNA sequencing. We conducted a comparative analysis between this post-COVID-19 cohort and the pre-infection dataset from the same participants. Community composition analysis, indicator species analysis, alpha diversity assessment, beta diversity exploration, and functional prediction were evaluated.ResultsThe Shannon and Simpson indexes of the oral microbial community declined significantly in the post-COVID-19 group when compared with the pre-infection cohort. Moreover, there was clear intergroup clustering between the two groups. In the post-COVID-19 group, the phylum Firmicutes showed a significant increase. Further, there were clear differences in relative abundance of several bacterial genera in contrast with the pre-infection group, including Streptococcus, Gemella, Granulicatella, Capnocytophaga, Leptotrichia, Fusobacterium, and Prevotella. We identified Gemella enrichment in the post-COVID-19 group, potentially serving as a recovery period performance indicator. Functional prediction revealed lipopolysaccharide biosynthesis downregulation in the post-COVID-19 group, an outcome with host inflammatory response modulation and innate defence mechanism implications.ConclusionDuring the recovery phase of COVID-19, the oral microbiome diversity of front-line healthcare workers failed to fully return to its pre-infection state. Despite the negative COVID-19 test result one month later, notable disparities persisted in the composition and functional attributes of the oral microbiota.

BackgroundIdentifying the diagnosis as well as prognosis for patients presented with community-acquired pneumonia (CAP) remains challenging. We aimed to identify the role of lysophosphatidylcholine acyl-transferase (LPCAT) for CAP along with assessing this protein’s effectiveness as a biomarker for severity of disease and mortality.MethodsProspective multicenter research study was carried out among hospitalized patients. A total of 299 CAP patients (including 97 severe CAP patients [SCAP]) and 20 healthy controls (HC) were included. A quantitative enzyme-linked immunosorbent test kit was employed for detecting the LPCAT level in plasma. We developed a deep-learning-based binary classification (SCAP or non-severe CAP [NSCAP]) model to process LPCAT levels and other laboratory test results.ResultsThe level of LPCAT in patients with SCAP and death outcome was significantly higher than that in other patients. LPCAT showed the highest predictive value for SCAP. LPCAT was able to predict 30-day mortality among CAP patients, combining LPCAT values with PSI scores or CURB-65 further enhance mortality prediction accuracy.ConclusionThe on admission level of LPCAT found significantly raised among SCAP patients and strongly predicted SCAP patients but with no correlation to etiology. Combining the LPCAT value with CURB-65 or PSI improved the 30-day mortality forecast significantly.Trial registrationNCT03093220 Registered on March 28th, 2017.

Abstract The environment of healthcare institutes (HCIs) potentially affects the internal microecology of medical workers, which is reflected not only in the well-studied gut microbiome but also in the more susceptible oral microbiome. We conducted a prospective cross-sectional cohort study in four hospital departments in Central China. Oropharyngeal swabs from 65 healthcare workers were collected and analyzed using 16S rRNA gene amplicon sequencing. The oral microbiome of healthcare workers exhibited prominent deviations in diversity, microbial structure, and predicted function. The coronary care unit (CCU) samples exhibited robust features and stability, with significantly higher abundances of genera such as Haemophilus, Fusobacterium, and Streptococcus, and a lower abundance of Prevotella. Functional prediction analysis showed that vitamin, nucleotide, and amino acid metabolisms were significantly different among the four departments. The CCU group was at a potential risk of developing periodontal disease owing to the increased abundance of F. nucleatum. Additionally, oral microbial diversification of healthcare workers was related to seniority. We described the oral microbiome profile of healthcare workers in different clinical scenarios and demonstrated that community diversity, structure, and potential functions differed markedly among departments. Intense modulation of the oral microbiome of healthcare workers occurs because of their original departments, especially in the CCU.

BackgroundOral microbiota is closely related to the homeostasis of the oral cavity and lungs. To provide potential information for the prediction, screening, and treatment strategies of individuals, this study compared and investigated the bacterial signatures in periodontitis and chronic obstructive pulmonary disease (COPD).Materials and methodsWe collected subgingival plaque and gingival crevicular fluid samples from 112 individuals (31 healthy controls, 24 patients with periodontitis, 28 patients with COPD, and 29 patients with both periodontitis and COPD). The oral microbiota was analyzed using 16S rRNA gene sequencing and diversity and functional prediction analysis were performed.ResultsWe observed higher bacterial richness in individuals with periodontitis in both types of oral samples. Using LEfSe and DESeq2 analyses, we found differentially abundant genera that may be potential biomarkers for each group. Mogibacterium is the predominant genus in COPD. Ten genera, including Desulfovibrio, Filifactor, Fretibacterium, Moraxella, Odoribacter, Pseudoramibacter Pyramidobacter, Scardovia, Shuttleworthia and Treponema were predominant in periodontitis. Bergeyella, Lautropia, Rothia, Propionibacterium and Cardiobacterium were the signature of the healthy controls. The significantly different pathways in the Kyoto Encyclopedia of Genes and Genomes (KEGG) between healthy controls and other groups were concentrated in genetic information processing, translation, replication and repair, and metabolism of cofactors and vitamins.ConclusionsWe found the significant differences in the bacterial community and functional characterization of oral microbiota in periodontitis, COPD and comorbid diseases. Compared to gingival crevicular fluid, subgingival plaque may be more appropriate for reflecting the difference of subgingival microbiota in periodontitis patients with COPD. These results may provide potentials for predicting, screening, and treatment strategies for individuals with periodontitis and COPD.

Abstract Background Hand injury is commonly associated with multiple soft tissue defects. Polyfoliate flaps grafting is the optimal approach for multiple wounds.The feasibility of clinical using of free thoracodorsal artery polyfoliate perforator flaps for repairing multiple soft tissue defects in the hand needs to be confirmed in clinical practice. Methods Fifteen patients with hand soft tissue defects that were repaired using free thoracodorsal artery polyfoliate perforator flaps from January 2015 to February 2018 was retrospectively analysed. The survival rate, the operative time, the appearance and sensory recovery of the flaps, and hand function were evaluated. Results The flaps of all 15 patients survived. Vascular crisis occurred in one patient, and the flap was saved after exploratory operation. The 15 patients were followed up for 12–26 months. Sensation in the flaps was partially recovered in all 15 patients. The wound in the donor area was closed directly with sutures. Mean score of scars at the donor site were assessed using the modified Vancouver scar scale (VSS) was 2.7. A puffed appearance in the recipient area was noted in four patients. To obtain a more satisfactory appearance, revision of the flap was performed once in these four patients. The Total Active Movement (TAM) evaluation system was used to assess the results, which were considered excellent in seven patients, good in six patients, fair in two patients, and poor in none of the patients. Ten of the 15 patients returned to their primary jobs. Conclusion Free thoracodorsal artery polyfoliate perforator flaps are appropriate for repairing multiple soft tissue defects in the hand, offer a satisfactory appearance, require a short operative time, and have little impact on the function and aesthetics of the donor site.

The aim of the present study was to determine the expression of MCP-1 in injured cartilage tissues, peripheral blood and synovial fluid from patients with cartilage injury of elbow joint of upper limbs, and try to understand its relationship with microRNA (miRNA or miR)-421. Twenty-eight patients and 26 healthy subjects were included. Injured cartilage tissues and peripheral blood were collected from all 28 patients. Synovial fluid was collected from 12 patients with elbow effusion. The expression of mRNA and miR-421 was determined by quantitative real-time polymerase chain reaction (qRT-PCR); the expression of MCP-1 protein in tissues, by western blotting; MCP-1 in serum or synovial fluid, by enzyme-linked immunosorbent assay (ELISA). Dual luciferase reporter assay was used to identify direct interaction between miR-421 and MCP-1. The migration of THP-1 cells was determined by transwell assay. The results showed that MCP-1 was elevated in patients with cartilage injury of elbow joint of upper limbs. By contrast, miR-421 was decreased. miR-421 could bind with the 3′-UTR seed region of MCP-1 mRNA to regulate its expression. Overexpression of miR-421 inhibited the expression of MCP-1 in HC-a cells, and the chemotaxis of THP-1 monocytes. This study demonstrates that the up-regulation of MCP-1 in injured cartilage tissues, serum and synovial fluid from patients with cartilage injury of elbow joint of upper limbs was related to the down-regulation of miR-421. In addition, miR-421 may affect the chemotaxis of monocytes via MCP-1, and regulate the local immune responses in injured cartilage site of elbow joint of upper limbs.

Background: Identifying the diagnosis as well as prognosis for patients presented with community-acquired pneumonia (CAP) remains challenging. We aimed to identify the role of lysophosphatidylcholine acyl-transferase (LPCAT) for CAP along with assessing this protein's effectiveness as a biomarker for severity of disease and mortality. Methods: Prospective multicenter research study was carried out among hospitalized patients. A total of 299 CAP patients (including 97 severe CAP patients [SCAP]) and 20 healthy controls (HC) were included. A quantitative enzyme-linked immunosorbent test kit was employed for detecting the LPCAT level in plasma. We developed a deep-learning-based binary classification (SCAP or non-severe CAP [NSCAP]) model to process LPCAT levels and other laboratory test results. Results: The level of LPCAT in patients with SCAP and death outcome was significantly higher than that in other patients. LPCAT showed the highest predictive value for SCAP. LPCAT was able to predict 30-day mortality among CAP patients, combining LPCAT values with PSI scores or CURB-65 further enhance mortality prediction accuracy. Conclusion: The on admission level of LPCAT found significantly raised among SCAP patients and strongly predicted SCAP patients but with no correlation to etiology. Combining the LPCAT value with CURB-65 or PSI improved the 30-day mortality forecast significantly. Trial registration: NCT03093220 Registered on March 28th, 2017. [ABSTRACT FROM AUTHOR]