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Sheep and goats are commonly infected with three Cryptosporidium species, including Cryptosporidium parvum, Cryptosporidium ubiquitum, and Cryptosporidium xiaoi, which differ from each in prevalence, geographic distribution, and public health importance. While C. parvum appears to be a dominant species in small ruminants in European countries, its occurrence in most African, Asian, and American countries appear to be limited. As a result, zoonotic infections due to contact with lambs and goat kids are common in European countries, leading to frequent reports of outbreaks of cryptosporidiosis on petting farms. In contrast, C. xiaoi is the dominant species elsewhere, and mostly does not infect humans. While C. ubiquitum is another zoonotic species, it occurs in sheep and goats at much lower frequency. Host adaptation appears to be present in both C. parvum and C. ubiquitum, consisting of several subtype families with different host preference. The host-adapted nature of C. parvum and C. ubiquitum has allowed the use of subtyping tools in tracking infection sources. This has led to the identification of geographic differences in the importance of small ruminants in epidemiology of human cryptosporidiosis. These tools have also been used effectively in linking zoonotic transmission of C. parvum between outbreak cases and the suspected animals. Further studies should be directly elucidating the reasons for differences in the distribution and public health importance of major Cryptosporidium species in sheep and goats.

Type 2 diabetes mellitus (T2DM) is a systematic multi‐organ metabolic disease, which is characterized by the dynamic interplay among different organs. The increasing incidence of T2DM reflects an urgent need for the development of in vitro human‐relevant models for disease study and drug therapy. Here, a new microfluidic multi‐organoid system is developed that recapitulates the human liver‐pancreatic islet axis in normal and disease states. The system contains two compartmentalized regions connected by a microchannel network, enabling 3D co‐culture of human induced pluripotent stem cells (hiPSC)‐derived liver and islet organoids for up to 30 days under circulatory perfusion conditions. The co‐cultured liver and islet organoids exhibit favorable growth and improved tissue‐specific functions. Transcriptional analyses reveal the activation of metabolically relevant signaling pathways in the co‐cultured organoids. Notably, the co‐culture system facilitates sensitive glucose‐stimulated insulin secretion from islet organoids and increased glucose utilization in liver organoids by glucose tolerance tests. Both liver and islet organoids display mitochondrial dysfunction and decreased glucose transport capacity under high glucose conditions, which can be alleviated by metformin treatment. This novel multi‐organoid system can recapitulate human‐relevant liver‐islet axis under both physiological and pathological conditions, providing a unique platform for future T2DM research and drug development. Type 2 diabetes mellitus (T2DM) is a systematic metabolic disease, which is characterized by the dynamic interplay among different organs. Here, a new microfluidic multi‐organoid system is developed from human induced pluripotent stem cells to recapitulate the liver‐pancreatic islet axis in normal and disease states. It provides a unique platform for T2DM research and drug development.

The current outbreak of coronavirus disease-2019 (COVID-19) poses unprecedented challenges to global health 1 . The new coronavirus responsible for this outbreak—severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)—shares high sequence identity to SARS-CoV and a bat coronavirus, RaTG13 2 . Although bats may be the reservoir host for a variety of coronaviruses 3 , 4 , it remains unknown whether SARS-CoV-2 has additional host species. Here we show that a coronavirus, which we name pangolin-CoV, isolated from a Malayan pangolin has 100%, 98.6%, 97.8% and 90.7% amino acid identity with SARS-CoV-2 in the E, M, N and S proteins, respectively. In particular, the receptor-binding domain of the S protein of pangolin-CoV is almost identical to that of SARS-CoV-2, with one difference in a noncritical amino acid. Our comparative genomic analysis suggests that SARS-CoV-2 may have originated in the recombination of a virus similar to pangolin-CoV with one similar to RaTG13. Pangolin-CoV was detected in 17 out of the 25 Malayan pangolins that we analysed. Infected pangolins showed clinical signs and histological changes, and circulating antibodies against pangolin-CoV reacted with the S protein of SARS-CoV-2. The isolation of a coronavirus from pangolins that is closely related to SARS-CoV-2 suggests that these animals have the potential to act as an intermediate host of SARS-CoV-2. This newly identified coronavirus from pangolins—the most-trafficked mammal in the illegal wildlife trade—could represent a future threat to public health if wildlife trade is not effectively controlled. A newly identified coronavirus found in Malayan pangolins shares considerable sequence identity with SARS-CoV-2, which suggests that the latter may have originated from a recombination event involving SARS-related coronaviruses from bats and pangolins.

Background Female breast cancer, cervical cancer, uterine cancer, and ovarian cancer (FBCUO) pose a significant threat to global public health. Data from the Global Burden of Disease, Injuries, and Risk Factors Study (GBD) 2021 provide critical insights that can guide the understanding and management of these cancers. Our study aims to offer comprehensive global, regional, and national estimates of the FBCUO cancer burden and its attributable risk factors from 1990 to 2021, as well as project future incidence trends up to 2050. These projections are essential for developing targeted prevention and control strategies, thereby informing more effective public health interventions. Methods Incidence, age-standardised incidence rate (ASIR), deaths, age-standardised mortality rate (ASMR), disability-adjusted life years (DALYs), age-standardised rate of DALYs (ASDR), and the burden due to risk factors associated with FBCUO cancer were analysed from 1990 to 2021, and the Bayesian APC model was utilized for forecasting future epidemiological trajectories. All statistical analyses were performed using Join-point software (version 4.9.1.0). Results Between 1990 to 2021, the global incidence, death, and DALYs, of female breast, cervical, uterine and ovarian cancer both to varying degrees of elevation. However, the ASMR and ASDR both showed a decreasing trend for FBCUO cancer. In 2021, diet high in red meat was a major risk factor for female breast cancer DALYs, but the attributable ASDR for diet high in red meat decreased from 1990 to 2021. Unsafe sex was the leading risk factor for cervical cancer DALYs, high body-mass index were the leading risk factor for uterine cancer and ovarian cancer. Projections indicate a global increase in the total number of female breast cancer and ovarian cancer cases from 2021 to 2050. In contrast, both cervical cancer and uterine cancer are expected to show downward trends over the same period. Conclusions The burden attributable to FBCUO cancers has increased significantly in female populations from 1990 to 2021, underscoring the urgent need for targeted measures to mitigate this trend. Meanwhile, Annual Percentage Change (APC) analysis indicates that the age-standardized incidence rates (ASIR) for female breast and ovarian cancers may continue to rise from 2022 to 2050. This projection highlights the importance of timely interventions to address these growing challenges.

Glioma is one of the most aggressive and highly fatal diseases with an extremely poor prognosis. Considering the poor clinical response to therapy in glioma, it is urgent to establish an in vitro model to facilitate the screening and assessment of anti-brain-tumor drugs. The blood–brain barrier (BBB), as well as liver metabolism plays an important role in determining the pharmacological activity of many anti-brain-tumor drugs. In this work, we designed a multi-interface liver-brain chip integrating co-culture system to assess hepatic metabolism dependent cytotoxicity of anti-brain-tumor drug in vitro. This microdevice composed of three microchannels which were separated by porous membrane and collagen. HepG2 and U87 cells were cultured in separated channels as mimics of liver and glioblastoma. Brain microvascular endothelial cells (BMECS) and cerebral astrocytes were co-cultured on collagen to mimic the brain microvascular endothelial barrier. Three common anti-tumor drugs, paclitaxel (PTX), capecitabine (CAP) and temozolomide (TMZ), were evaluated on this chip. In integrated liver-brain chip, liver enhanced the cytotoxicity of CAP on U87 cells by 30%, but having no significant effect on TMZ. The BBB decreased the cytotoxicity of PTX by 20%, while no significant effects were observed on TMZ and CAP, indicating the importance of liver metabolism and blood–brain barrier on the evaluation of anti-brain-tumor drugs. This work provides a biomimetic liver-brain model to mimic the physiological and pharmacological processes in vitro and presents a simple platform for long-term cell co-culture, drug delivery and metabolism, and real-time analysis of drug effects on brain cancer.

Coronavirus disease 2019 (COVID‐19) is a global pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS‐CoV‐2). The models that can accurately resemble human‐relevant responses to viral infection are lacking. Here, a biomimetic human disease model on chip that allows to recapitulate lung injury and immune responses induced by SARS‐CoV‐2 in vitro at organ level is created. This human alveolar chip reproduce the key features of alveolar‐capillary barrier by coculture of human alveolar epithelium, microvascular endothelium, and circulating immune cells under fluidic flow in normal and disease. Upon SARS‐CoV‐2 infection, the epithelium exhibits higher susceptibility to virus than endothelium. Transcriptional analyses show activated innate immune responses in epithelium and cytokine‐dependent pathways in endothelium at day 3 post‐infection, revealing the distinctive responses in different cell types. Notably, viral infection causes the immune cell recruitment, endothelium detachment, and increased inflammatory cytokines release, suggesting the crucial role of immune cells involved in alveolar barrier injury and exacerbated inflammation. Treatment with remdesivir can inhibit viral replication and alleviate barrier disruption on chip. This organ chip model can closely mirror human‐relevant responses to SARS‐CoV‐2 infection, which is difficult to be achieved by in vitro models, providing a unique platform for COVID‐19 research and drug development. Coronavirus disease 2019 (COVID‐19) is a global pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS‐CoV‐2). Here, a biomimetic human alveolar infection model is built using organ chip that allows to recapitulate the lung injury and immune responses induced by SARS‐CoV‐2 at organ level. It provides a unique and rapid platform to accelerate COVID‐19 research and drug development.

Background Cryptosporidiosis is a major cause of gastrointestinal diseases in humans and other vertebrates. Previous analyses of invasion-related proteins revealed that Cryptosporidium parvum , Cryptosporidium hominis , and Cryptosporidium ubiquitum mainly differed in copy numbers of secreted MEDLE proteins and insulinase-like proteases and sequences of mucin-type glycoproteins. Recently, Cryptosporidium chipmunk genotype I was identified as a novel zoonotic pathogen in humans. In this study, we sequenced its genome and conducted a comparative genomic analysis. Results The genome of Cryptosporidium chipmunk genotype I has gene content and organization similar to C. parvum and other intestinal Cryptosporidium species sequenced to date. A total of 3783 putative protein-encoding genes were identified in the genome, 3525 of which are shared by Cryptosporidium chipmunk genotype I and three major human-pathogenic Cryptosporidium species, C. parvum , C. hominis , and Cryptosporidium meleagridis . The metabolic pathways are almost identical among these four Cryptosporidium species. Compared with C. parvum , a major reduction in gene content in Cryptosporidium chipmunk genotype I is in the number of telomeric genes encoding MEDLE proteins (two instead of six) and insulinase-like proteases (one instead of two). Highly polymorphic genes between the two species are mostly subtelomeric ones encoding secretory proteins, most of which have higher dN/dS ratios and half are members of multiple gene families. In particular, two subtelomeric ABC transporters are under strong positive selection. Conclusions Cryptosporidium chipmunk genotype I possesses genome organization, gene content, metabolic pathways and invasion-related proteins similar to the common human-pathogenic Cryptosporidium species, reaffirming its human-pathogenic nature. The loss of some subtelomeric genes encoding insulinase-like proteases and secreted MEDLE proteins and high sequence divergence in secreted pathogenesis determinants could contribute to the biological differences among human-pathogenic Cryptosporidium species.

Virulence factor genes (VFGs) play pivotal roles in bacterial infections and have been identified within the human gut microbiota. However, their involvement in chronic diseases remains poorly understood. Here, we establish an expanded VFG database (VFDB 2.0) consisting of 62,332 nonredundant orthologues and alleles of VFGs using species-specific average nucleotide identity ( https://github.com/Wanting-Dong/MetaVF_toolkit/tree/main/databases ). We further develop the MetaVF toolkit, facilitating the precise identification of pathobiont-carried VFGs at the species level. A thorough characterization of VFGs for 5452 commensal isolates from healthy individuals reveals that only 11 of 301 species harbour these factors. Further analyses of VFGs within the gut microbiomes of nine chronic diseases reveal both common and disease-specific VFG features. Notably, in type 2 diabetes patients, long HiFi sequencing confirms that shared VF features are carried by pathobiont strains of Escherichia coli and Klebsiella pneumoniae . These findings underscore the critical importance of identifying and understanding VFGs in microbiome-associated diseases. Here, by mining 18,521 complete bacterial genomes, the authors construct VFDB 2.0, an expanded database of virulence factor genes, consisting of 62,332 nonredundant orthologues and alleles with annotated host taxa using species-specific average nucleotide identity, and present MetaVF, a toolkit that facilitates precise identification and quantification of virulence factor genes carried by specific pathobionts in human gut metagenomes.

Over 200 cryptosporidiosis outbreaks have been reported, but little is known if other enteric pathogens were also involved in some of these outbreaks. Recently, an outbreak of cryptosporidiosis linked to poor hygiene by two Cryptosporidium hominis subtypes occurred in a pediatric hospital ward (Ward A) in China, lasting for more than 14 months. In this study, the concurrence during the outbreak of three other enteric pathogens with a similar transmission route, Giardia duodenalis, Enterocytozoon bieneusi, and Clostridium difficile, was assessed. The occurrence of G. duodenalis, E. bieneusi, and C. difficile in 78 inpatients from Ward A and 283 and 216 inpatients from two control wards (Wards C and D) in the same hospital was examined using molecular diagnostic tools. Significantly higher infection rates were found in children in Ward A for all study pathogens than in Wards C and D (P<0.01): 9.5% versus 1.4% and 0% for G. duodenalis, 10.8% versus 2.8% and 3.7% for E. bieneusi, and 60.8% versus 37.8% and 27.8% for C. difficile, respectively. These differences were mostly seen in children ≤ 12 months. Enteric pathogen-positive children in Ward A (31/58 or 53.4%) were more likely to have mixed infections than those in Ward C (4/119 or 3.4%) or D (5/68, 7.4%; P<0.01). Having cryptosporidiosis was a risk factor for G. duodenalis (OR = 4.3; P = 0.08), E. bieneusi (OR = 3.1; P = 0.04), and C. difficile (OR = 4.7; P<0.01) infection. In addition, a lower diversity of G. duodenalis, E. bieneusi, and C. difficile genotypes/subtypes was observed in Ward A. Data from this study suggest that multiple pathogens were concurrently present during the previous cryptosporidiosis outbreak. Examination of multiple enteric pathogens should be conducted when poor hygiene is the likely cause of outbreaks of diarrhea.

Limited data are available on infection rates and genetic identity of Enterocytozoon bieneusi and Giardia duodenalis in horses and donkeys. In this study, 865 fecal specimens were collected from donkeys (n = 540) and horses (n = 325) in three provinces and autonomous regions in northern China during 2015–2019. Enterocytozoon bieneusi was detected and genotyped by PCR and sequence analyses of the ribosomal internal transcribed spacer (ITS) and G. duodenalis was detected and genotyped by PCR and sequence analyses of the β-giardin, glutamate dehydrogenase, and triosephosphate isomerase genes. The overall infection rates of E. bieneusi and G. duodenalis were 21.9% (118/540) and 11.5% (62/540) in donkeys, and 7.4% (24/325) and 2.8% (9/325) in horses, respectively. These differences in infection rates of E. bieneusi and G. duodenalis between donkeys and horses were significant (χ2 = 30.9, df = 1, P < 0.0001; χ2 = 20.4, df = 1, P < 0.0001, respectively). By age, the 28.9% infection rate of E. bieneusi in donkeys under 6 months was significantly higher than that in animals over 6 months (6.0%; χ2 = 35.2, df = 1, P < 0.0001). In contrast, donkeys of 6–12 months had higher infection rate (35.9%) of G. duodenalis than donkeys under 6 months (9.9%; χ2 = 22.1, df = 1, P < 0.0001) and over 12 months (8.7%; χ2 = 17.3, df = 1, P < 0.0001). In horses, animals of > 12 months had significantly higher infection rate (31.1%) of E. bieneusi than horses under 6 months (3.4%; χ2 = 29.4, df = 1, P < 0.0001) and 6–12 months (3.8%; χ2 = 26.1, df = 1, P < 0.0001). Twenty genotypes of E. bieneusi were detected, including six known ones and 14 new genotypes. Among them, nine genotypes in 45% E. bieneusi–positive specimens belonged to the zoonotic group 1. Similarly, three G. duodenalis assemblages were detected, including A (in 2 horses and 30 donkeys), B (in 6 horses and 29 donkeys), and E (in 1 horse); three donkeys had coinfections of assemblages A and B. The assemblage A isolates identified all belong to the sub-assemblage AI. These results indicate that unlike in other farm animals, there is a common occurrence of zoonotic E. bieneusi and G. duodenalis genotypes in horses and donkeys.