The ongoing pandemic of coronavirus disease 19 (COVID-19) is caused by a newly discovered β coronavirus named severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). How long the adaptive immunity triggered by SARS-CoV-2 can last is of critical clinical relevance in assessing the probability of second infection and efficacy of vaccination. Here we examined, using ELISA, the IgG antibodies in serum specimens collected from 17 COVID-19 patients at 6–7 months after diagnosis and the results were compared to those from cases investigated 2 weeks to 2 months post-infection. All samples were positive for IgGs against the S- and N-proteins of SARS-CoV-2. Notably, 14 samples available at 6–7 months post-infection all showed significant neutralizing activities in a pseudovirus assay, with no difference in blocking the cell-entry of the 614D and 614G variants of SARS-CoV-2. Furthermore, in 10 blood samples from cases at 6–7 months post-infection used for memory T-cell tests, we found that interferon γ-producing CD4⁺ and CD8⁺ cells were increased upon SARS-CoV-2 antigen stimulation. Together, these results indicate that durable anti-SARS-CoV-2 immunity is common in convalescent population, and vaccines developed from 614D variant may offer protection from the currently predominant 614D variant of SARS-CoV-2.

The coronavirus disease 2019 (COVID-19) caused by SARS-CoV-2 was identified in December 2019. The symptoms include fever, cough, dyspnea, early symptom of sputum, and acute respiratory distress syndrome (ARDS). Mesenchymal stem cell (MSC) therapy is the immediate treatment used for patients with severe cases of COVID-19. Herein, we describe two confirmed cases of COVID-19 in Wuhan to explore the role of MSC in the treatment of COVID-19. MSC transplantation increases the immune indicators (including CD4 and lymphocytes) and decreases the inflammation indicators (interleukin-6 and C-reactive protein). High-flow nasal cannula can be used as an initial support strategy for patients with ARDS. With MSC transplantation, the fraction of inspired O₂ (FiO₂) of the two patients gradually decreased while the oxygen saturation (SaO₂) and partial pressure of oxygen (PO₂) improved. Additionally, the patients’ chest computed tomography showed that bilateral lung exudate lesions were adsorbed after MSC infusion. Results indicated that MSC transplantation provides clinical data on the treatment of COVID-19 and may serve as an alternative method for treating COVID-19, particularly in patients with ARDS.

Triple-negative breast cancer (TNBC) is the most aggressive subtype of breast cancer with a heterogeneous genetic profile. Chemotherapy exhibits substantial activity in a small subset of these patients. Drug resistance is inevitable. Major progress has been made in the genetic analysis of TNBC to identify novel targets and increase the precision of therapeutic intervention. Such progress has translated into major advances in treatment strategies, including modified chemotherapy approaches, immune checkpoint inhibitors, and targeted therapeutic drugs. All of these strategies have been evaluated in clinical trials. Nevertheless, patient selection remains a considerable challenge in clinical practice.

An unexpected observation among the COVID-19 pandemic is that smokers constituted only 1.4%−18.5% of hospitalized adults, calling for an urgent investigation to determine the role of smoking in SARS-CoV-2 infection. Here, we show that cigarette smoke extract (CSE) and carcinogen benzo(a)pyrene (BaP) increase ACE2 mRNA but trigger ACE2 protein catabolism. BaP induces an aryl hydrocarbon receptor (AhR)-dependent upregulation of the ubiquitin E3 ligase Skp2 for ACE2 ubiquitination. ACE2 in lung tissues of non-smokers is higher than in smokers, consistent with the findings that tobacco carcinogens downregulate ACE2 in mice. Tobacco carcinogens inhibit SARS-CoV-2 spike protein pseudovirions infection of the cells. Given that tobacco smoke accounts for 8 million deaths including 2.1 million cancer deaths annually and Skp2 is an oncoprotein, tobacco use should not be recommended and cessation plan should be prepared for smokers in COVID-19 pandemic.

The possible effects of angiotensin-converting enzyme inhibitors (ACEIs) or angiotensin II receptor blockers (ARBs) on COVID-19 disease severity have generated considerable debate. We performed a single-center, retrospective analysis of hospitalized adult COVID-19 patients in Wuhan, China, who had definite clinical outcome (dead or discharged) by February 15, 2020. Patients on anti-hypertensive treatment with or without ACEI/ARB were compared on their clinical characteristics and outcomes. The medical records from 702 patients were screened. Among the 101 patients with a history of hypertension and taking at least one anti-hypertensive medication, 40 patients were receiving ACEI/ARB as part of their regimen, and 61 patients were on anti-hypertensive medication other than ACEI/ARB. We observed no statistically significant differences in percentages of in-hospital mortality (28% vs. 34%, P=0.46), ICU admission (20% vs. 28%, P=0.37) or invasive mechanical ventilation (18% vs. 26%, P=0.31) between patients with or without ACEI/ARB treatment. Further multivariable adjustment of age and gender did not provide evidence for a significant association between ACEI/ARB treatment and severe COVID-19 outcomes. Our findings confirm the lack of an association between chronic receipt of renin-angiotensin system antagonists and severe outcomes of COVID-19. Patients should continue previous anti-hypertensive therapy until further evidence is available.

Coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has caused a global pandemic in only 3 months. In addition to major respiratory distress, characteristic neurological manifestations are also described, indicating that SARS-CoV-2 may be an underestimated opportunistic pathogen of the brain. Based on previous studies of neuroinvasive human respiratory coronaviruses, it is proposed that after physical contact with the nasal mucosa, laryngopharynx, trachea, lower respiratory tract, alveoli epithelium, or gastrointestinal mucosa, SARS-CoV-2 can induce intrinsic and innate immune responses in the host involving increased cytokine release, tissue damage, and high neurosusceptibility to COVID-19, especially in the hypoxic conditions caused by lung injury. In some immune-compromised individuals, the virus may invade the brain through multiple routes, such as the vasculature and peripheral nerves. Therefore, in addition to drug treatments, such as pharmaceuticals and traditional Chinese medicine, non-pharmaceutical precautions, including facemasks and hand hygiene, are critically important.

Diabetes mellitus is one of the major public health problems worldwide. Considerable recent evidence suggests that the cellular reduction–oxidation (redox) imbalance leads to oxidative stress and subsequent occurrence and development of diabetes and related complications by regulating certain signaling pathways involved in β-cell dysfunction and insulin resistance. Reactive oxide species (ROS) can also directly oxidize certain proteins (defined as redox modification) involved in the diabetes process. There are a number of potential problems in the clinical application of antioxidant therapies including poor solubility, storage instability and non-selectivity of antioxidants. Novel antioxidant delivery systems may overcome pharmacokinetic and stability problem and improve the selectivity of scavenging ROS. We have therefore focused on the role of oxidative stress and antioxidative therapies in the pathogenesis of diabetes mellitus. Precise therapeutic interventions against ROS and downstream targets are now possible and provide important new insights into the treatment of diabetes.

Coronavirus disease 2019 (COVID-19) is currently under a global pandemic trend. The efficiency of containment measures and epidemic tendency of typical countries should be assessed. In this study, the efficiency of prevention and control measures in China, Italy, Iran, South Korea, and Japan was assessed, and the COVID-19 epidemic tendency among these countries was compared. Results showed that the effective reproduction number(Re) in Wuhan, China increased almost exponentially, reaching a maximum of 3.98 before a lockdown and rapidly decreased to below 1 due to containment and mitigation strategies of the Chinese government. The Re in Italy declined at a slower pace than that in China after the implementation of prevention and control measures. The Re in Iran showed a certain decline after the establishment of a national epidemic control command, and an evident stationary phase occurred because the best window period for the prevention and control of the epidemic was missed. The epidemic in Japan and South Korea reoccurred several times with the Re fluctuating greatly. The epidemic has hardly rebounded in China due to the implementation of prevention and control strategies and the effective enforcement of policies. Other countries suffering from the epidemic could learn from the Chinese experience in containing COVID-19.

Post-transplantation cyclophosphamide (PT-Cy) alone or in combination with other immunosuppressive drugs has emerged as a promising strategy in the setting of allogeneic hematopoietic stem cell transplantation. Improved survival rate was reported in lymphoid malignancies following PT-Cy strategy compared with myeloid disease in non-myeloablative bone marrow transplant setting. Thus, we aimed to evaluate the safety and efficacy of PT-Cy combined with cyclosporine as graft-versus-host disease (GVHD) prophylaxis after myeloablative conditioning and T cell-replete peripheral stem cell transplantation in lymphoid malignancies. This single-arm phase II clinical trial (NCT01435447) involving 31 adult patients was conducted from January 2013 to June 2018. The donor-type neutrophil engraftment rate was 100%, and the overall incidence of grade II to IV and grade III to IV acute GVHD was 39% and 24%, respectively. The cumulative incidence rates of chronic GVHD (35%), including moderate to severe forms (10%), were reduced compared with those of the historical group (P=0.03 and P=0.04, respectively). With a median follow-up of 18 months, the estimated 2-year overall and event-free survival was 64.8% (95% confidence interval: 47.8%–86.7%) and 58.4% (95% CI: 41.9%–81.7%), respectively. The 2-year cumulative incidence rate of relapse was 19.5% (95% CI: 9.0%–35.8%), whereas the non-relapse mortality rate was 21.8% (95% CI: 11.3%–38.1%). These results demonstrated the feasibility of PT-Cy as GVHD prophylaxis in this clinical setting. This strategy could significantly reduce the incidence of chronic GVHD and its moderate to severe forms but not of acute GVHD and results in similar survival outcomes compared with the historical group. A prospective study with additional patients is warranted to confirm the role of PT-Cy in lymphoid malignancy.

deep learning (DL) has achieved state-of-the-art performance in many digital pathology analysis tasks. Traditional methods usually require hand-crafted domain-specific features, and DL methods can learn representations without manually designed features. In terms of feature extraction, DL approaches are less labor intensive compared with conventional machine learning methods. In this paper, we comprehensively summarize recent DL-based image analysis studies in histopathology, including different tasks (e.g., classification, semantic segmentation, detection, and instance segmentation) and various applications (e.g., stain normalization, cell/gland/region structure analysis). DL methods can provide consistent and accurate outcomes. DL is a promising tool to assist pathologists in clinical diagnosis.

Berberine, an isoquinoline alkaloid isolated from the Chinese herb Coptis chinensis and other Berberis plants, has a wide range of pharmacological properties. Berberine can be used to treat many diseases, such as cancer and digestive, metabolic, cardiovascular, and neurological diseases. Berberine has protective capacities in digestive diseases. It can inhibit toxins and bacteria, including Helicobacter pylori, protect the intestinal epithelial barrier from injury, and ameliorate liver injury. Berberine also inhibits the proliferation of various types of cancer cells and impedes invasion and metastasis. Recent evidence has confirmed that berberine improves the efficacy and safety of chemoradiotherapies. In addition, berberine regulates glycometabolism and lipid metabolism, improves energy expenditure, reduces body weight, and alleviates nonalcoholic fatty liver disease. Berberine also improves cardiovascular hemodynamics, suppresses ischemic arrhythmias, attenuates the development of atherosclerosis, and reduces hypertension. Berberine shows potent neuroprotective effects, including antioxidative, antiapoptotic, and anti-ischemic. Furthermore, berberine exerts protective effects against other diseases. The mechanisms of its functions have been extensively explored, but much remains to be clarified. This article summarizes the main pharmacological actions of berberine and its mechanisms in cancer and digestive, metabolic, cardiovascular, and neurological diseases.

Artificial intelligence (AI) is gradually changing the practice of surgery with technological advancements in imaging, navigation, and robotic intervention. In this article, we review the recent successful and influential applications of AI in surgery from preoperative planning and intraoperative guidance to its integration into surgical robots. We conclude this review by summarizing the current state, emerging trends, and major challenges in the future development of AI in surgery.

The coronavirus disease 2019 (COVID-19) has become a life-threatening pandemic. The epidemic trends in different countries vary considerably due to different policy-making and resources mobilization. We calculated basic reproduction number (R₀) and the time-varying estimate of the effective reproductive number (R_t) of COVID-19 by using the maximum likelihood method and the sequential Bayesian method, respectively. European and North American countries possessed higher R₀ and unsteady R_t fluctuations, whereas some heavily affected Asian countries showed relatively low R₀ and declining R_t now. The numbers of patients in Africa and Latin America are still low, but the potential risk of huge outbreaks cannot be ignored. Three scenarios were then simulated, generating distinct outcomes by using SEIR (susceptible, exposed, infectious, and removed) model. First, evidence-based prompt responses yield lower transmission rate followed by decreasing R_t. Second, implementation of effective control policies at a relatively late stage, in spite of huge casualties at early phase, can still achieve containment and mitigation. Third, wisely taking advantage of the time-window for developing countries in Africa and Latin America to adopt adequate measures can save more people’s life. Our mathematical modeling provides evidence for international communities to develop sound design of containment and mitigation policies for COVID-19.

Post-translational modification of cellular proteins by ubiquitin regulates numerous cellular processes, including cell division, immune responses, and apoptosis. Ubiquitin-mediated control over these processes can be reversed by deubiquitinases (DUBs), which remove ubiquitin from target proteins and depolymerize polyubiquitin chains. Recently, much progress has been made in the DUBs. In humans, the ovarian tumor protease (OTU) subfamily of DUBs includes 16 members, most of which mediate cell signaling cascades. These OTUs show great variation in structure and function, which display a series of mechanistic features. In this review, we provide a comprehensive analysis of current progress in character, structure and function of OTUs, such as the substrate specificity and catalytic activity regulation. Then we discuss the relationship between some diseases and OTUs. Finally, we summarize the structure of viral OTUs and their function in immune escape and viral survival. Despite the challenges, OTUs might provide new therapeutic targets, due to their involvement in key regulatory processes.

Traditional Chinese medicine (TCM), an ancient system of alternative medicine, played an active role in the prevention and control of COVID-19 in China. It improved the clinical symptoms of patients, reduced the mortality rate, improved the recovery rate, and effectively relieved the operating pressure on the national medical system during critical conditions. In light of the current global pandemic, TCM-related measures might open up a new channel in the control of COVID-19 in other countries and regions. Here, we summarize the TCM-related measures that were widely used in China, including TCM guidelines, the Wuchang pattern, mobile cabin hospitals, integrated treatment of TCM and modern medicine for critical patients, and non-medicine therapy for convalescent patients, and describe how TCM effectively treated patients afflicted with the COVID-19. Effective TCM therapies could, therefore, be recommended and practiced based on the existing medical evidence from increased scientific studies.

High-throughput metabolomics can clarify the underlying molecular mechanism of diseases via the qualitative and quantitative analysis of metabolites. This study used the established Yang Huang syndrome (YHS) mouse model to evaluate the efficacy of geniposide (GEN). Urine metabolic data were quantified by ultra-performance liquid chromatography–tandem mass spectrometry. The non-target screening of the massive biological information dataset was performed, and a total of 33 metabolites, including tyramine glucuronide, aurine, and L-cysteine, were identified relating to YHS. These differential metabolites directly participated in the disturbance of phase I reaction and hydrophilic transformation of bilirubin. Interestingly, they were completely reversed by GEN. While, as the auxiliary technical means, we also focused on the molecular prediction and docking results in network pharmacological and integrated analysis part. We used integrated analysis to communicate the multiple results of metabolomics and network pharmacology. This study is the first to report that GEN indirectly regulates the metabolite “tyramine glucuronide” through its direct effect on the target heme oxygenase 1 in vivo. Meanwhile, heme oxygenase-1, a prediction of network pharmacology, was the confirmed metabolic enzyme of phase I reaction in hepatocytes. Our study indicated that the combination of high-throughput metabolomics and network pharmacology is a robust combination for deciphering the pathogenesis of the traditional Chinese medicine (TCM) syndrome.

As a promising method in artificial intelligence, deep learning has been proven successful in several domains ranging from acoustics and images to natural language processing. With medical imaging becoming an important part of disease screening and diagnosis, deep learning-based approaches have emerged as powerful techniques in medical image areas. In this process, feature representations are learned directly and automatically from data, leading to remarkable breakthroughs in the medical field. Deep learning has been widely applied in medical imaging for improved image analysis. This paper reviews the major deep learning techniques in this time of rapid evolution and summarizes some of its key contributions and state-of-the-art outcomes. The topics include classification, detection, and segmentation tasks on medical image analysis with respect to pulmonary medical images, datasets, and benchmarks. A comprehensive overview of these methods implemented on various lung diseases consisting of pulmonary nodule diseases, pulmonary embolism, pneumonia, and interstitial lung disease is also provided. Lastly, the application of deep learning techniques to the medical image and an analysis of their future challenges and potential directions are discussed.

Coronavirus disease 2019 (COVID-19), which is caused by severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2), has spread around the world. However, approaches to distinguish COVID-19 from pneumonia caused by other pathogens have not yet been reported. We retrospectively analyzed the clinical data of 97 children with probable COVID-19. A total of 13 (13.4%) patients were confirmed positive for SARS-CoV-2 infection by nucleic acid RT-PCR testing, and 41 (42.3%) patients were found to be infected with other pathogens. Notably, no pathogen was detected in 43 (44.3%) patients. Among all patients, 25 (25.8%) had familial cluster exposure history, and 52 (53.6%) had one or more coexisting conditions. Fifteen (15.5%) patients were admitted or transferred to the PICU. In the 11 confirmed COVID-19 cases, 5 (45.5%) and 7 (63.6%) were positive for IgM and IgG against SARS-CoV-2, respectively. In 22 patients with suspected COVID-19, 1 (4.5%) was positive for IgG but negative for IgM. The most frequently detected pathogen was Mycoplasma pneumonia (29, 29.9%). One patient with confirmed COVID-19 died. Our results strongly indicated that the detection of asymptomatic COVID-19 or coexisting conditions must be strengthened in pediatric patients. These cases may be difficult to diagnose as COVID-19 unless etiologic analysis is conducted. A serologic test can be a useful adjunctive diagnostic tool in cases where SARS-CoV-2 infection is highly suspected but the nucleic acid test is negative.

Minimally invasive surgery, including laparoscopic and thoracoscopic procedures, benefits patients in terms of improved postoperative outcomes and short recovery time. The challenges in hand–eye coordination and manipulation dexterity during the aforementioned procedures have inspired an enormous wave of developments on surgical robotic systems to assist keyhole and endoscopic procedures in the past decades. This paper presents a systematic review of the state-of-the-art systems, picturing a detailed landscape of the system configurations, actuation schemes, and control approaches of the existing surgical robotic systems for keyhole and endoscopic procedures. The development challenges and future perspectives are discussed in depth to point out the need for new enabling technologies and inspire future researches.

The association between serum uric acid and the risk of incident diabetes in Chinese adults remains unknown. This study aimed to investigate this association in a community-dwelling population aged≥40 years in Shanghai, China. Oral glucose tole3rance test was conducted during baseline and follow-up visits. Relative risk regression was utilized to examine the associations between baseline gender-specific serum uric acid levels and incident diabetes risk. A total of 613 (10.3%) incident diabetes cases were identified during the follow-up visit after 4.5 years. Fasting plasma glucose, postload glucose, and glycated hemoglobin A1c during the follow-up visit progressively increased across the sex-specific quartiles of serum uric acid (all Ps<0.05). The incidence rate of diabetes increased across the quartiles of serum uric acid (7.43%, 8.77%, 11.47%, and 13.43%). Multivariate adjusted regression analysis revealed that individuals in the highest quartile had 1.36-fold increased risk of diabetes compared with those in the lowest quartile of serum uric acid (odds ratio (95% confidence interval) = 1.36 (1.06−1.73)). Stratified analysis indicated that the association was only observed in women. Accordingly, serum uric acid was associated with the increased risk of incident diabetes among middle-aged and elderly Chinese women.

Coronavirus disease 2019 (COVID-19) is now pandemic worldwide and has heavily overloaded hospitals in Wuhan City, China during the time between late January and February. We reported the clinical features and therapeutic characteristics of moderate COVID-19 cases in Wuhan that were treated via the integration of traditional Chinese medicine (TCM) and Western medicine. We collected electronic medical record (EMR) data, which included the full clinical profiles of patients, from a designated TCM hospital in Wuhan. The structured data of symptoms and drugs from admission notes were obtained through an information extraction process. Other key clinical entities were also confirmed and normalized to obtain information on the diagnosis, clinical treatments, laboratory tests, and outcomes of the patients. A total of 293 COVID-19 inpatient cases, including 207 moderate and 86 (29.3%) severe cases, were included in our research. Among these cases, 238 were discharged, 31 were transferred, and 24 (all severe cases) died in the hospital. Our COVID-19 cases involved elderly patients with advanced ages (57 years on average) and high comorbidity rates (61%). Our results reconfirmed several well-recognized risk factors, such as age, gender (male), and comorbidities, as well as provided novel laboratory indications (e.g., cholesterol) and TCM-specific phenotype markers (e.g., dull tongue) that were relevant to COVID-19 infections and prognosis. In addition to antiviral/antibiotics and standard supportive therapies, TCM herbal prescriptions incorporating 290 distinct herbs were used in 273 (93%) cases. The cases that received TCM treatment had lower death rates than those that did not receive TCM treatment (17/273= 6.2% vs. 7/20= 35%, P = 0.0004 for all cases; 17/77= 22% vs. 7/9= 77.7%, P = 0.002 for severe cases). The TCM herbal prescriptions used for the treatment of COVID-19 infections mainly consisted of Pericarpium Citri Reticulatae, Radix Scutellariae, Rhizoma Pinellia, and their combinations, which reflected the practical TCM principles (e.g., clearing heat and dampening phlegm). Lastly, 59% of the patients received treatment, including antiviral, antibiotics, and Chinese patent medicine, before admission. This situation might have some effects on symptoms, such as fever and dry cough. By using EMR data, we described the clinical features and therapeutic characteristics of 293 COVID-19 cases treated via the integration of TCM herbal prescriptions and Western medicine. Clinical manifestations and treatments before admission and in the hospital were investigated. Our results preliminarily showed the potential effectiveness of TCM herbal prescriptions and their regularities in COVID-19 treatment.

We report the clinical and laboratory findings and successful management of seven patients with critical coronavirus disease 2019 (COVID-19) requiring mechanical ventilation (MV). The patients were diagnosed based on epidemiological history, clinical manifestations, and nucleic acid testing. Upon diagnosis with COVID-19 of critical severity, the patients were admitted to the intensive care unit, where they received early noninvasive–invasive sequential ventilation, early prone positioning, and bundle pharmacotherapy regimen, which consists of antiviral, anti-inflammation, immune-enhancing, and complication-prophylaxis medicines. The patients presented fever (n = 7, 100%), dry cough (n = 3, 42.9%), weakness (n = 2, 28.6%), chest tightness (n = 1, 14.3%), and/or muscle pain (n = 1, 14.3%). All patients had normal or lower than normal white blood cell count/lymphocyte count, and chest computed tomography scans showed bilateral patchy shadows or ground glass opacity in the lungs. Nucleic acid testing confirmed COVID-19 in all seven patients. The median MV duration and intensive care unit stay were 9.9 days (interquartile range, 6.5–14.6 days; range, 5–17 days) and 12.9 days (interquartile range, 9.7–17.6 days; range, 7–19 days), respectively. All seven patients were extubated, weaned off MV, transferred to the common ward, and discharged as of the writing of this report. Thus, we concluded that good outcomes for patients with critical COVID-19 can be achieved with early noninvasive–invasive sequential ventilation and bundle pharmacotherapy.

Disorders of sex development (DSD) are a group of rare complex clinical syndromes with multiple etiologies. Distinguishing the various causes of DSD is quite difficult in clinical practice, even for senior general physicians because of the similar and atypical clinical manifestations of these conditions. In addition, DSD are difficult to diagnose because most primary doctors receive insufficient training for DSD. Delayed diagnoses and misdiagnoses are common for patients with DSD and lead to poor treatment and prognoses. On the basis of the principles and algorithms of dynamic uncertain causality graph (DUCG), a diagnosis model for DSD was jointly constructed by experts on DSD and engineers of artificial intelligence. “Chaining” inference algorithm and weighted logic operation mechanism were applied to guarantee the accuracy and efficiency of diagnostic reasoning under incomplete situations and uncertain information. Verification was performed using 153 selected clinical cases involving nine common DSD-related diseases and three causes other than DSD as the differential diagnosis. The model had an accuracy of 94.1%, which was significantly higher than that of interns and third-year residents. In conclusion, the DUCG model has broad application prospects as a computer-aided diagnostic tool for DSD-related diseases.

Radiation therapy (RT) is widely used to treat cancer. Technological advances in RT have occurred in the past 30 years. These advances, such as three-dimensional image guidance, intensity modulation, and robotics, created challenges and opportunities for the next breakthrough, in which artificial intelligence (AI) will possibly play important roles. AI will replace certain repetitive and labor-intensive tasks and improve the accuracy and consistency of others, particularly those with increased complexity because of technological advances. The improvement in efficiency and consistency is important to manage the increasing cancer patient burden to the society. Furthermore, AI may provide new functionalities that facilitate satisfactory RT. The functionalities include superior images for real-time intervention and adaptive and personalized RT. AI may effectively synthesize and analyze big data for such purposes. This review describes the RT workflow and identifies areas, including imaging, treatment planning, quality assurance, and outcome prediction, that benefit from AI. This review primarily focuses on deep-learning techniques, although conventional machine-learning techniques are also mentioned.

This study aimed to investigate the correlation between serum miR-154-5p and urinary albumin to creatinine ratio (UACR) in patients with type 2 diabetes mellitus (T2DM) and the association with biomarkers of inflammation and fibrosis in diabetic kidney disease (DKD). A total of 390 patients with T2DM were divided into three groups: normal albuminuria (UACR<30 mg/g, n=136, NA), microalbuminuria (UACR at 30–300 mg/g, n=132, MA), and clinical albuminuria (UACR>300 mg/g, n=122, CA). Circulating miR-154-5p, inflammatory (C-reactive protein (CRP); erythrocyte sedimentation rate (ESR); and tumor necrosis factor-α (TNF-α) and fibrotic markers (vascular endothelial growth factor (VEGF); transforming growth factor-β1 (TGF-β1); and fibronectin (FN)), and other biochemical indicators were assessed via real-time PCR, enzyme-linked immunosorbent assay, and chemiluminescence assay in patients with T2DM and 138 control subjects (NC). UACR, miR-154-5p, glycated hemoglobin (HbA1c), serum creatinine (sCr), blood urea nitrogen (BUN), ESR, CRP, VEGF, TNF-α, TGF-β1, and FN were significantly higher and the estimated glomerular filtration rate (eGFR) was significantly lower in NA, MA, and CA groups than in NC subjects (P<0.05). Elevated levels of UACR and miR-154-5p were directly correlated with HbA1c, sCr, BUN, ESR, CRP, VEGF, TNF-α, TGF-β1, and FN and negatively correlated with eGFR (P<0.05). miR-154-5p, HbA1c, sCr, BUN, eGFR, ESR, CRP, VEGF, TNF-α, TGF-β1, and FN were important factors affecting UACR. These findings indicated that elevated serum miR-154-5p is significantly correlated with high UACR in patients with T2DM and may offer a novel reference for the early diagnosis of DKD.

The huge communities of microorganisms that symbiotically colonize humans are recognized as significant players in health and disease. The human microbiome may influence prostate cancer development. To date, several studies have focused on the effect of prostate infections as well as the composition of the human microbiome in relation to prostate cancer risk. Current studies suggest that the microbiota of men with prostate cancer significantly differs from that of healthy men, demonstrating that certain bacteria could be associated with cancer development as well as altered responses to treatment. In healthy individuals, the microbiome plays a crucial role in the maintenance of homeostasis of body metabolism. Dysbiosis may contribute to the emergence of health problems, including malignancy through affecting systemic immune responses and creating systemic inflammation, and changing serum hormone levels. In this review, we discuss recent data about how the microbes colonizing different parts of the human body including urinary tract, gastrointestinal tract, oral cavity, and skin might affect the risk of developing prostate cancer. Furthermore, we discuss strategies to target the microbiome for risk assessment, prevention, and treatment of prostate cancer.

Breast cancer is one of the most common malignancies that seriously threaten women’s health. In the process of the malignant transformation of breast cancer, metabolic reprogramming and immune evasion represent the two main fascinating characteristics of cancer and facilitate cancer cell proliferation. Breast cancer cells generate energy through increased glucose metabolism. Lipid metabolism contributes to biological signal pathways and forms cell membranes except energy generation. Amino acids act as basic protein units and metabolic regulators in supporting cell growth. For tumor-associated immunity, poor immunogenicity and heightened immunosuppression cause breast cancer cells to evade the host’s immune system. For the past few years, the complex mechanisms of metabolic reprogramming and immune evasion are deeply investigated, and the genes involved in these processes are used as clinical therapeutic targets for breast cancer. Here, we review the recent findings related to abnormal metabolism and immune characteristics, regulatory mechanisms, their links, and relevant therapeutic strategies.

Artificial intelligence (AI) is coming to medicine in a big wave. From making diagnosis in various medical conditions, following the latest advancements in scientific literature, suggesting appropriate therapies, to predicting prognosis and outcome of diseases and conditions, AI is offering unprecedented possibilities to improve care for patients. Gastroenterology is a field that AI can make a significant impact. This is partly because the diagnosis of gastrointestinal conditions relies a lot on image-based investigations and procedures (endoscopy and radiology). AI-assisted image analysis can make accurate assessment and provide more information than conventional analysis. AI integration of genomic, epigenetic, and metagenomic data may offer new classifications of gastrointestinal cancers and suggest optimal personalized treatments. In managing relapsing and remitting diseases such as inflammatory bowel disease, irritable bowel syndrome, and peptic ulcer bleeding, convoluted neural network may formulate models to predict disease outcome, enhancing treatment efficacy. AI and surgical robots can also assist surgeons in conducting gastrointestinal operations. While the advancement and new opportunities are exciting, the responsibility and liability issues of AI-assisted diagnosis and management need much deliberations.

This study aimed to evaluate the efficacy of Chinese herbal medicine (CHM) in patients with severe/critical coronavirus disease 2019 (COVID-19). In this retrospective study, data were collected from 662 patients with severe/critical COVID-19 who were admitted to a designated hospital to treat patients with severe COVID-19 in Wuhan before March 20, 2020. All patients were divided into an exposed group (CHM users) and a control group (non-users). After propensity score matching in a 1:1 ratio, 156 CHM users were matched by propensity score to 156 non-users. No significant differences in seven baseline clinical variables were found between the two groups of patients. All-cause mortality was reported in 13 CHM users who died and 36 non-users who died. After multivariate adjustment, the mortality risk of CHM users was reduced by 82.2% (odds ratio 0.178, 95% CI 0.076–0.418; P<0.001) compared with the non-users. Secondly, age (odds ratio 1.053, 95% CI 1.023–1.084; P<0.001) and the proportion of severe/critical patients (odds ratio 0.063, 95% CI 0.028–0.143; P<0.001) were the risk factors of mortality. These results show that the use of CHM may reduce the mortality of patients with severe/critical COVID-19.