Infertility has become a global public health issue. In vitro fertilization and embryo transfer (IVF-ET) is widely performed as an infertility treatment. However, a significant number of infertile women continue to experience serial implantation failure, despite the high quality of the transferred embryos. Jian-Pi-An-Tai formula is an experience formula in treating threatened abortion in our team. It has also been used to treat infertile women after embryo transfer and shows superiority compared to single use of conventional western medicine. However, the of evidence on its effective in treating infertile women undergo IVF-ET is lacking.This randomized controlled trial (RCT) will be carried out in Hangzhou TCM Hospital Affiliated to Zhejiang Chinese Medical University planning to recruit 180 infertile patients undergoing IVF-ET with the type of deficiency of both the spleen and kidney. The control group will be treated by conventional western medicine and the treatment group will use conventional western medicine plus Jian-Pi-An-Tai formula. The primary outcomes will include Embryo implantation rate, Clinical pregnancy rate, Persistent pregnancy rate; and the secondary outcomes will include TCM symptom score and reproductive hormones. Safety evaluation will be recorded during the whole study. All data in this RCT will be analyzed by SPSS 23.0 software. This study has been approved by the Research Ethics Committee of the Hangzhou TCM Hospital Affiliated to Zhejiang Chinese Medical University (2022KY130).The results of this RCT will contribute to provide scientific and rigorous evidence for the efficacy and safety of Jian-Pi-An-Tai formula in treating infertile women undergo IVF-ET. And the results from this RCT will be published in a relevant journal after finished. Numerous factors, including hormonal imbalance, genetics, diet, smoking, caffeine use, and alcohol consumption, are linked to infertility. In vitro fertilization and embryo transfer (IVF-ET) is widely performed as an infertility treatment worldwide, resulting in the births of more than 5 million infants worldwide. Despite the remarkable advancements in assisted reproductive technology (ART), a significant number of infertile women continue to experience serial implantation failure, despite the high quality of the transferred embryos. In addition, women conceived through IVF-ET have a higher rate of threatened abortions than natural pregnancy. It is crucial to improve the implantation rate and reduce the abortion rate after embryo transfer for the success of IVF-ET.Couples who have a normal sexual life but do not conceive naturally for more than a year are considered to have infertility. Infertility has become the third most serious disease, making it a global public health issue. A healthy pregnancy is built on a foundation of appropriate implantation processes, which are facilitated by optimal receptivity. Endocrine reasons, inflammatory events, thin endometria, fibroids, polyps, septa, and immunologically induced abnormalities are only a few of the contributing elements that affect receptivity. Although implantation failure in IVF-ET is a very common occurrence, there are currently no evidence-based therapeutic treatments available. Therefore, current therapy approaches are mostly empirical, based on some biologic justification, but have scant clinical proof to back them up.,6The process of embryo implantation, which involves both the embryo and the mother’s endometrium, is intricate. One of the main causes of unsuccessful embryo implantation is assumed to be impaired endometrial receptivity.Numerous clinical and experimental studies have demonstrated the effectiveness of the traditional Chinese medicine in the prevention and treatment of recurrent spontaneous abortion, in increasing the number and quality of high-quality embryos, in repairing endometrium, and in improving uterine receptivity.–11 The spleen and kidney are the foundation of acquired constitution and congenital constitution respectively. Along with the spleen, the spleen governs transportation and transformation, generating qi and blood for the entire body. The main cause of the embryo’s failure to develop normally is deficiency of both the spleen and kidney.Chinese herbal medicines have been widely used in Asian countries for millennia to treat a variety of reproductive problems, and they hold promise for the future of human reproductive health, notably in the treatment of recurrent miscarriage and ART drugs.Jian-Pi-An-Tai formula is an experience formula in treating threatened abortion (Deficiency of both the spleen and kidney type) for more than 50 years in our team. In recent years, Jian-Pi-An-Tai formula has also been used to treat infertile women after embryo transfer and shows superiority compared to single use of conventional western medicine. However, the of evidence on its effective in treating infertile women undergo IVF-ET is lacking. Therefore, the aim of this study is to verify the clinical efficacy and safety of Jian-Pi-An-Tai formula for the pregnancy outcome of IVF-ET in infertile women.This study is a protocol for a randomized, non-blinded, controlled clinical trial. A total of 180 infertile patients with the type of Deficiency of both spleen and kidney will be conducted according to the flow diagram and will last for near 2 years, scheduled to start from January 2023 ;Suffering from sexually transmitted diseases or acute inflammation of urogenital system;Patients with serious primary diseases such as cardiovascular, cerebrovascular, kidney, liver and hematopoietic system;Patients with serious cognitive impairment and mental illness;Long term exposure to toxic and harmful substances such as radiation or chemicals;Incomplete data or unauthorized use of other treatments;Patients who are allergic to the drugs used in this study.The randomization succession will be created with the PROC PLAN strategy explanations of SAS programming 9.3 bundle by the analyst specialists of Zhejiang Chinese Clinical College, and will be hidden and scattered utilizing obscure envelopes. During the time spent treating and analyzing the data, these specialists will not be involved. By phone, the clinical investigators will apply for a new included patient’s randomization number. The doctors and patients engaged in this RCT won’t likely be rendered blind because there is no usage of herbal medicine in the control group.The randomization strategy will be used to divide the participants into one of the 2 groups.The treatment group: conventional western medicine after embryo transplantation combined with Jian-Pi-An-Tai formula. Jian-Pi-An-Tai formula is composed of codonopsis pilosula, astragalus membranaceus, fried atractylodes macrocephala, donkey hide gelatin, mulberry parasitic, dodder seed, raw rehmannia root, cooked rehmannia root, ramie root, scutellaria baicalensis, paeony root, wolfberry fruit, eclipta alba, perilla frutescens stem, licorice root, and dipsacus, which provided by Preparation Center of the Hangzhou TCM Hospital Affiliated to Zhejiang Chinese Medical University. The patients are planned to take Jian-Pi-An-Tai formula for 5 weeks.The control group: conventional western medicine after embryo transplantation.Embryo implantation rate: number of embryos implanted/total number of embryos transferred * 100%. Blood sampling test of β-HCG will be taken on the 8th and 10th days after embryo transfer. Positive results can be determined as successful embryo implantation.Clinical pregnancy rate: number of clinical pregnancies/number of implanted embryos * 100%. Doppler ultrasound will be taken on the 5th week after embryo transfer. Gestational sac and fetal heart beat can be determined as successful clinical pregnancy.Persistent pregnancy rate: number of cycles of continuous pregnancy/number of embryos implanted * 100%. Doppler ultrasound will be taken on the 12th week after embryo transfer. Existence of fetal heart beat can be determined as successful persistent pregnancy.The form of TCM symptom will be measured at the baseline, after 5 weeks of treatment.Blood sampling test of β-HCG, estradiol (E2), progesterone (P) levels will be measured once a week after embryo implantation, and additional tests should be conducted at any time according to the clinical needs.Blood sampling test of liver function and blood routine examination will be conducted before, during, and after treatment of Jian-Pi-An-Tai formula.The number of participants is capable to detecting according to the results of the previous study  with an alpha error of 0.05 and beta error of 0.2. Considering the 10% drop-out rates, the sample will be composed of 180 participants randomized into 2 groups.P values less than .05 are considered statistically significant. The description of quantitative indicators will calculate the number of cases, mean, standard deviation, median, minimum and maximum. Classification indicators are described by the number of cases and percentages of each category. Normally distributed data is represented by mean ± standard deviation, and non-normally distributed data is represented by median and interquartile range. Comparisons between groups of measurement data will be conducted by using independent sample t test, and within group differences will be tested with paired t test. Differences between groups of numeration data will be assessed with chi-square test.The statistical analysis of this study will be conducted by statisticians of the Zhejiang Chinese Medical University. Software packages SPSS 23.0 and SAS 9.3 will be used for statistical analysis. All statistical tests will be conducted by 2-sided tests and  An increasing number of families are opting for IVF-ET to get pregnancy. However, what we are facing today is that implantation failure and threatened abortion in IVF-ET is common, but we lack the evidence-based therapeutic solutions for treating it.Over the past 10 years, the rate of infertility has significantly increased, making it a significant public health issue for women of reproductive age worldwide. Infertility brings families heavy economic and psychological burden, affecting social harmony and stability. In addition, a recent meta-analysis demonstrates that intimate partner violence against infertile women occurs frequently, particularly in low- and middle-income countries.In China, the application of Chinese herbal medicines go through the process of IVF-ET, well known for its economical, safe and no side effects. Chinese herbal medicines shows a significant effect on improving endometrial receptivity, added to these are regulating hormone secretion, improving oocyte quality, relieving patients’ anxiety, and reducing inflammation. However, there is insufficient and poor-quality evidence to support its efficacy in treating infertile IVF-ET patients. Hence, randomized controlled trials are necessary to provide higher evidence for clinical use. The trial is valuable for it may provide scientific and rigorous evidence for the efficacy and safety of Jian-Pi-An-Tai formula in treating infertile women undergo IVF-ET.All authors read and critically revised the protocol.Conceptualization: Qing Liu, Liuqing Yang, Qin Zhang.Data curation: Ran Cheng, Qing Liu, Liuqing Yang.Formal analysis: Ying Zhu, Ying Zhao.Investigation: Qin Zhang.Methodology: Ran Cheng, Liuqing Yang.Supervision: Qin Zshang.Validation: Yi-Zhe Zhang.Writing – original draft: Ran Cheng, Qing Liu.Writing – review & editing: Ran Cheng, Qing Liu, Liuqing Yang, Qin Zhang.


The first set includes 1.5 million tweets containing alcohol-related keywords, while the second set does not contain such references. LIWC software analyzed the tweets for sentiment factors. ANCOVAs were used to determine whether language use significantly differed between the sets, considering differences in the pandemic period (before or after the pandemic declaration) while controlling for the number of tweets. The study found that tweets in the 40 days after March 11, 2020 contained more authentic language, more affiliation-oriented language, and exhibited more positive emotion than tweets in the 40 days pre-declaration. Alcohol-related status was a significant factor only when tweets contained personal concerns, regardless of pandemic period. Authenticity levels increased significantly in alcohol-related tweets post-declaration. The findings suggest alcohol may play a lesser role in the expression of psychological, social, and emotional sentiment than the pandemic period, but interaction between authentic language and alcohol references may reflect an increased use of alcohol for coping.This study explores pandemic-related changes in Twitter communication by examining differences in emotional, psychological and social sentiment between alcohol-related tweets and a random sample of non-alcohol tweets during the onset of the COVID-19 pandemic. Two equivalent size sets of English-language, COVID-specific tweets posted between February 1 The COVID-19 pandemic has resulted in a plethora of societal changes, including changes in social patterns , economic patterns , and in how work and learning are performed (increased use of remote work and videoconferencing tools). Initial research has found vast emotional, psychological, and social impacts as a result of these abrupt and severe changes to daily life brought about by the onset of the pandemic. Specifically, research has demonstrated increased prevalence of mental health issues , and an Increased emotional and psychological stress has been shown to increase chances of substance abuse, including alcohol. General life stress and stress related to catastrophic events can lead to an increase in alcohol consumption and an increased risk for alcohol use disorders . The onsThe purpose of this study was to identify comparative differences in emotional, psychological and social sentiment between alcohol-related tweets and a random sample of non-alcohol-related tweets through the initial onset of the pandemic . Identifying these differences can shed light on how the onset of the pandemic influenced Twitter communication, specifically emotional, psychological, and social references and sentiment. It was expected that alcohol-related tweets would exhibit increased levels of language reflecting honesty and confidence than unrelated tweets in the post-pandemic period (post-March 11), indicating a potential use of alcohol as coping mechanism for pandemic-induced stress. It was further expected that COVID-related social isolation would cause alcohol-related tweets to include more emotional and affiliation-oriented language than unrelated tweets during this same period. Finally, it was anticipated that alcohol-related tweets would include more references to personal concerns , given the increased likelihood of occupational and financial uncertainty during the early days of the pandemic.th, 2020, when the virus was declared a pandemic by the World Health Organization, COVID-19 rapidly spread to over 114 countries. The initial onset of the pandemic resulted in world-wide government mandates intended to slow the spread of the virus . These changes disrupted daily life for people worldwide, and with these abrupt changes came many sources of stress with far-reaching consequences. Looking back on the initial impact of the pandemic can provide insight into its continuing effects and may provide some foreshadowing of the issues that arise as individuals begin to phase back into normal routines.Between late 2019, when the COVID-19 virus was first confirmed in Wuhan China, and March 11Mental health issues quickly increased during the early days of the pandemic (see ) includiBeyond mental health concerns, the initial onset of the pandemic also resulted in a range of personal concerns. Internationally, most individuals experienced a loss of financial opportunities due to a complete loss or reduction in employment hours . In the Each of these identified impacts has inarguably led to an increase in stress for most of the world’s population (see ). As a rAs previously demonstrated, the onset of the global pandemic has resulted in an increase in general life stress as well as stress related to the catastrophic effects of the pandemic. Previous research has demonstrated that exposure to both types of stress can result in increases in alcohol consumption and an increased risk for alcohol use disorders . AlcoholSome coping strategies that can serve as a buffer against alcohol consumption include the use of adaptive problem-focused strategies , 20 and Prior research on events resulting in community-wide disruptions have also pointed toward alcohol use as a common coping strategy among those impacted. For example, research has shown that alcohol consumption increases following economic crises  as well Assessing alcohol references within social media may provide an efficient method for capturing the use of alcohol as a means of coping with the effects of the pandemic. Previous research has effectively demonstrated the use of social media content to reflect alcohol consumption behaviors . Beyond The analysis of social media posts to assess the well-being of populations has been accepted as a viable alternative to more traditional survey-based research . TwitterThe constantly accessible yet asynchronous nature of social media provides opportunities for self-disclosure and relationship-building that may be more palatable than more traditional, synchronous communication methods. Social media provides a comparatively easy mechanism for building a large social network and associated social capital through the reduction of spatial and temporal constraints . Prior rTweets referencing personal situations, emotions, and struggles can be expected during crisis events, including pandemics . Prior rPrior research into the impact of catastrophic events on emotional tone often find at least a temporary increase in negative emotionality  though pAnalytical Thinking, Emotional Tone, Clout, and Authenticity. Rather than specific predefined categories, these summary variables represent composites of select others on a 0–100 scale [Assessing the content of tweets can provide insight into the emotional, psychological, and behavioral state of the communicator. The Linguistic Inquiry and Word Count (LIWC) software provides automated analysis of text-based data for pre-defined affective, cognitive, structural, and behavioral constructs using approximately 80 predefined linguistic categories .00 scale .This study explores changes in Twitter communication surrounding the onset of the COVID-19 pandemic. Specifically, this study used LIWC software to identify comparative differences in emotional, psychological and social sentiment between a set of alcohol-related tweets and a random sample of non-alcohol-related tweets from February through April, 2020. This study focused on linguistic analysis of tweets to answer the following research questions:1: Do tweets containing alcohol-related references exhibit significant differences in the level of honesty and confidence when compared to non-alcohol tweets, accounting for the pandemic period (pre- and post-)?RQ2: Do tweets containing alcohol-related references exhibit significant differences in emotional tone when compared to non-alcohol tweets, accounting for the pandemic period (pre- and post-)?RQ3: Do tweets containing alcohol-related references exhibit significant differences in the use of affiliation-oriented language when compared to non-alcohol tweets, accounting for the pandemic period (pre- and post-)?RQ4: Do tweets containing alcohol-related references exhibit significant differences in the use of language related to personal concerns when compared to non-alcohol tweets, accounting for the pandemic period (pre- and post-)?RQThis study builds on the prior work of , 50, 51,https://crisisnlp.qcri.org/covid19). The GeoCov19 dataset [http://github.com/DocNow/hydrator) was used to download the tweets of the available IDs. Some IDs were no longer accessible, but 84.85% of the provided IDs were successfully downloaded. Custom Python scripts were then used to convert the associated tweets into a format suitable for analysis. The resultant dataset included 242,550,744 English-language tweets . Additional custom Python scripts were used as a filter to extract tweets containing one or more of 60 alcohol keywords taken from the codebook established by Alhabash et al. [Tweets were collected for the period February 1st, 2020 through April 20th, 2020. Tweet IDs were obtained from the GeoCoV19 dataset provided by CrisisNLP  and on a per-day basis. Reservoir sampling was used to obtain the random sample (see ), given A series of 2 (pandemic period: pre-pandemic vs. post-pandemic) x 2  mixed Analysis of Covariance (ANCOVA) procedures were conducted to determine whether language use significantly differed between the set of alcohol-related tweets and the random sample of tweets without alcohol keywords, considering differences in the pandemic period while controlling for the overall number of tweets. The analyses were also used to determine if there were interactions between pandemic period and the alcohol-related status on language use. Given its long-standing use in similar analyses, LIWC was chosen as the tool to gather information on emotional, psychological, and social sentiment among the sample tweets. LIWC measures were computed for each day of the sample period, both for alcohol-related tweets and non-alcohol-related tweets.Authenticity, Clout, and Emotional Tone–while the final two models utilized composite measures constructed by the authors from more discrete LIWC measures. The decision to use a mix of existing summary measures and custom composites was made based on the preceding literature review, the general acceptance and validity of the existing LIWC measures, and the authors’ desire to identify comparative differences in emotional, psychological, and social sentiment at a more connected or abstract level rather than focusing on more discrete elements. A description and rationale for each of the dependent variables is provided in the following paragraphs.The dependent variables for these analyses were operationalized from existing LIWC measures. Five ANCOVA models were created. The first three models utilized summary measures provided by the LIWC software–Authenticity, Clout, and Emotional Tone summary variables represent standardized composites using previously published algorithms and findings, and values exist on a 0–100 scale [Authenticity measure considers the frequency of first-person singular and third-person pronouns, along with fewer exclusion words , and words expressing negative emotions [Authenticity measure is used as a proxy for honesty (research question 1), given that a higher Authenticity value suggests "a more honest, personal, and disclosing text" [The 00 scale , 46. Theemotions . In termemotions , includiemotions . For exaemotions  found thClout measure is used as a proxy for confidence (research question 1), given that a higher Clout value suggests “the author is speaking from the perspective of high expertise and is confident" [Clout measure was used as a proxy for confidence given that the COVID-19 pandemic has been shown to impact self-confidence, among other mental health concerns [The nfident"  whereas nfident" . The Cloconcerns . Self-coconcerns .Emotional Tone measure is used as the dependent variable for exploring research question 2; higher values represent a more positive emotional tone, whereas lower values represent a more negative tone. Values around the midpoint (50) represent ambivalence [Emotional Tone measure is constructed based on the number of negative (e.g. sadness) and positive words (e.g. happiness) in the corpus [The ivalence . The Emoe corpus . This mee corpus .Affiliation Concerns. The four LIWC measures used are affiliation , social processes , family references , and friend references . The Affiliation Concerns composite measure was chosen due to the impact of the pandemic on social processes, the aforementioned relationship between social affiliation and mental health [The remaining two ANCOVA models use dependent measures constructed as composites from existing LIWC measures. The use of affiliation-oriented language (research question 3) is operationalized as the sum of four separate LIWC measures and is named l health , 8 and dl health , and pril health .Personal Concerns measure (research question 4) was operationalized as the sum of six separate LIWC measures: work (e.g. job), leisure , home , money , religion , and death . The Personal Concerns measure provides an indication of the impact that COVID-19 has had on potential stressors relating to employment, finance, faith, and health [Finally, a d health –13. DescAuthenticity  = 12.880, p < 0.001, partial η2 = 0.143). No significant main effects were found for alcohol-related status  = 2.098, p = 0.152). The covariate  significantly influenced Authenticity, F = 7.136, p = 0.009, partial η2 = 0.085. The results show that users during the post-pandemic period used significantly more authentic language for both alcohol-related tweets  and tweets unrelated to alcohol  than during the pre-pandemic period , controlling for the overall total number of tweets. Estimated marginal means are shown in The ANCOVA results showed a significant main effect of the pandemic period (pre-pandemic vs. post-pandemic) on Authenticity  = 4.904, p = 0.030, partial η2 = 0.060). Estimated marginal means are shown in There was significant interaction between the alcohol status of tweet  and the pandemic period on In sum, these results show that tweets contained more authentic language (reflecting honest expression) in the post-pandemic period. While alcohol did not have a significant primary effect, the interaction between alcohol and the pandemic period suggests that authenticity levels increased significantly more in alcohol-related tweets during the post-pandemic period, perhaps reflecting an increased use of alcohol as a means of coping with the new reality.Clout  = 0.055, p = 0.815). No significant main effects were found for alcohol-related status  = 1.198, p = 0.170). The covariate  significantly influenced Clout, F = 7.309, p = 0.008, partial η2 = 0.087. There was no significant interaction between the alcohol status of tweet  and the pandemic period on Clout  = 0.543, p = 0.463) nor between the alcohol status and the total number of tweets  = 0.782, p = 0.379). The overall finding is that nether the pandemic period nor the alcohol-related status of the tweets significantly impacted the use of confidence-related language.The ANCOVA results did not show a significant main effect of the pandemic period on Emotional Tone  = 13.241, p < 0.001, partial η2 = 0.147). No significant main effects were found for alcohol-related status  = 0.047, p = 0.830). The covariate  did not significantly influence Emotional Tone, F = 1.749, p = 0.190. Therefore, ignoring other variables, emotional tone differed between alcohol- and non-alcohol-related tweets based on the pandemic period. Estimated marginal means are shown in The ANCOVA results showed a significant main effect of the pandemic period on Emotional Tone  = 0.207, p = 0.651) nor between the alcohol status and the total number of tweets  = 0.018, p = 0.893).The results show that tweets during the post-pandemic period had a significantly more positive emotional tone for both alcohol-related tweets  and tweets unrelated to alcohol  than during the pre-pandemic period , controlling for the overall total number of tweets. There was no significant interaction between the alcohol status of tweet  and the pandemic period on In sum, these results show that tweets contained more positive emotional tone in the post-pandemic period for both alcohol-related tweets and unrelated tweets. Alcohol status was not a significant factor.Affiliation Concerns  = 5.760, p < 0.05, partial η2 = 0.070). No significant main effects were found for alcohol-related status  = 0.510, p = 0.477). The covariate  did not significantly influence Affiliation Concerns, F = 2.166, p = 0.145. Therefore, ignoring other variables, the use of affiliation-oriented language differed between alcohol- and non-alcohol-related tweets based on the pandemic period. Estimated marginal means are shown in The ANCOVA results showed a significant main effect of the pandemic period on the use of language related to Affiliation Concerns  = 0.071, p = 0.791) or between the alcohol status and the total number of tweets  = 0.576, p = 0.450).The results show that tweets during the post-pandemic period had a significantly more affiliation-oriented language for both alcohol-related tweets  and tweets unrelated to alcohol  than during the pre-pandemic period , controlling for the overall total number of tweets. There was no significant interaction between the alcohol status of tweet  and the pandemic period on In sum, these results show that tweets contained more affiliation-oriented language in the post-pandemic period for both alcohol-related tweets and unrelated tweets. Alcohol status was again not a significant factor in the results.Personal Concerns  = 0.116, p = 0.734). A significant main effect was found for alcohol-related status  = 23.581, p < 0.001, partial η2 = 0.234). The covariate  did not significantly influence Personal Concerns, F = 1.211, p = 0.274.The ANCOVA results did not show a significant main effect of the pandemic period on the use of language related to Therefore, ignoring other variables, language related to personal concerns significantly differed between alcohol- and non-alcohol-related tweets. Estimated marginal means are shown in Personal Concerns  = 0.682, p = 0.411) or between the alcohol status and the total number of tweets  = 0.417, p = 0.520).There was no significant interaction between the alcohol status of tweet  and the pandemic period on The results show that personal concerns were more prevalent in alcohol-related tweets, regardless of the pandemic period. This result suggests that alcohol may be used as a coping mechanism for the insecurities  brought on by the emerging crisis, as well as accompanying references to other potential coping mechanisms .The social upheaval brought about by the COVID-19 pandemic has led to questions of how individuals have been coping with such dramatic and abrupt life changes. Of particular concern is that individuals will turn towards outlets such as alcohol which, if abused, can have negative physical and mental health outcomes. For example, prior research has shown that stressful situations can result in increased chances for substance abuse, including alcohol. By examining social media communication, this study intended to assess whether the presence of alcohol references in said communication aligned with different levels of emotional, psychological, and social sentiment, perhaps indicating that alcohol was increasingly used as coping mechanism during the onset of the pandemic.The study results found that the pandemic onset had a significant influence on the psychological, social, and emotional sentiment of COVID-related Twitter communication. Tweets in the post-pandemic period–the period after the WHO pandemic declaration in March 2020 –contained more honest (authentic) language, more affiliation-oriented language, and exhibited a more positive emotional tone. The increased use of language reflecting honesty can be reasonably expected; crises such as the COVID-19 pandemic can have a focusing impact on priorities and communication styles  which inThe positive emotional tone exhibited in post-pandemic tweets is consistent with prior research  which suThese findings are also consistent with prior research  which suThe study results found alcohol-related status to be a significant main effect factor in only one instance–when individuals tweeted about personal concerns –and this difference was consistent across both periods (pre- and post-pandemic). Prior research , 24 has While alcohol-related status was not a significant factor alone in regard to the use of honest (authentic) language within these tweets, alcohol status was found to have a significant interaction with the pandemic period; authenticity levels increased significantly more in alcohol-related tweets during the post-pandemic period than in tweets with no alcohol references. While the overall findings suggest that alcohol may play a lesser role in the expression of psychological, social, and emotional sentiment than the pandemic period, the interaction between the prevalence of honest (authentic) language and alcohol references may reflect an increased use of alcohol as a means of coping. This method of coping with the new reality associated with the onset of the pandemic, may have helped to either facilitate open and honest expression–as opposed to more tentative or guarded expression–or perhaps enabled individuals to endure the sometimes painful process of “opening up” during a time of crisis.There are three potential limitations associated with this research. First, the use of English-only tweets without geolocation limits the ability to generalize the findings to a specific area. The use of the pandemic declaration date  as a dividing line between the pre- and post-pandemic periods provides a common time reference, despite the differing impacts of the pandemic across nations. A second potential limitation is the comparatively short timeframe for data collection (80 days). This timeframe was based on the accessibility of publicly available data due to Twitter API restrictions and provides a balance between the emergence of the pandemic and its immediate impacts. Finally, it must be noted that references to alcohol within tweets may not reflect patterns in use. However, alcohol references may indicate a willingness to use alcohol and, thus, be predictive of future behavior. Prior research has supported using social media to predict behaviors, including but not limited to alcohol consumption e.g., , 64, 65), 6564, 6In conclusion, the current study represents, to our knowledge, the only investigation into alcohol use as a coping mechanism during the onset of the COVID-19 pandemic using content analysis of alcohol- related tweets. Social media outlets like Twitter can act as a lens by which individuals express both psychological characteristics as well as coping behaviors during crises, and the study results show differences in in the expression of psychological, social, and emotional sentiment based on time period (pre- and post-pandemic) and, in one instance, the presence of alcohol references. The results found that alcohol-related tweets following the onset of the pandemic did not reflect changes related to confidence, emotional tone, affiliation references, or personal concerns compared to non-alcohol associated tweets. However, alcohol-related tweets during the post-pandemic period did reflect a greater degree of authenticity/honesty. This result may reflect alcohol use as a means of coping with the abrupt and dramatic changes associated with the pandemic. Specifically, in alcohol- related tweets individuals appeared to use more candid language following the initial onset of the pandemic. Alcohol-related tweets were also more likely to include content related to personal concerns regardless of the pandemic period, providing potential further indication of alcohol use as a coping mechanism. Future research should examine whether alcohol use for coping has become more prevalent as the pandemic has continued to upset societal norms.


Insulin resistance (IR) is closely related to non-small-cell lung cancer (NSCLC) risk. Recently, triglyceride glucose-body mass index (TyG-BMI) has been recognized as one of the simple indexes of insulin resistance (IR). However, there are limited data on the relationship between TyG-BMI and NSCLC. Here, we investigated the association of TyG-BMI with NSCLC risk in Chinese adults.This study consisted of 477 NSCLC cases and 954 healthy subjects. All participants were enrolled from 3201 Hospital affiliated to the Medical Department of Xi’an Jiaotong University. TyG-BMI was calculated based on the values of fasting blood glucose, triglyceride, and BMI. The association of TyG-BMI with NSCLC risk was estimated by logistic regression analysis.P < 0.01). There was a significant positive association between TyG-BMI and NSCLC  after controlling for confounding factors. Moreover, the prevalence of NSCLC was significantly elevated in participants in the high TyG-BMI tertiles than those in the intermediate and low TyG-BMI tertiles . Importantly, TyG-BMI achieved a significant diagnostic accuracy for NSCLC, with an AUC (area under the curve) of 0.769 and a cutoff value of 184.87.The mean value of TyG-BMI was statistically increased in patients with NSCLC compared to the control group (201.11 ± 28.18 vs. 174 ± 23.78, The findings suggest that TyG-BMI is a useful tool for assessing NSCLC risk. Thus, it is essential to follow up on high TyG-BMI, and lifestyle modification is needed to prevent NSCLC in people with high TyG-BMI. Lung cancer has been alarmingly increasing and gaining more attention from many scholars, with non-small cell lung cancer (NSCLC) being the most common form . SmokingInsulin resistance (IR), characterized by hyperinsulinemia, is involved in the physiopathologic mechanism of metabolic-related diseases such as obesity, metabolic syndrome, and non-alcoholic fatty liver disease (NAFLD) , 5. MoreA retrospective review of medical records of 510 patients with newly diagnosed NSCLC who were enrolled between October 2010 and September 2018 at 3201 Hospital affiliated to the Medical Department of Xi’an Jiaotong University was carried out. The eligible patients for this study had histological or cytological confirmation of NSCLC. Locally advanced diseases were based on clinical assessments. Information regarding risk factors and medical history was collected by face-to-face consultation. History of cancer, diabetes, coronary heart disease, cerebrovascular disease, and thyroid disease were the exclusion criteria. In addition, we also excluded participants with a history of some relevant medication use, such as immunosuppressant and fenofibrate triglyceride-lowering drugs, as well as women who were pregnant or breastfeeding. After applying the exclusion criteria, a total of 477 patients with NSCLC (the NSCLC group) were enrolled in our final analysis. For each case, two apparently healthy controls matched for sex and age who underwent physical examination in the same period were enrolled in the study. The exclusion criteria for the controls were self-reported medical history and were the same as those of the cases. Finally, 954 controls participated in this study. All the participants provided written informed consent. The study was approved by the Human Research Ethics Committee of 3201 Hospital affiliated to Medical Department of Xi’an Jiaotong University .Clinical parameters and laboratory results were obtained from the medical records of all the subjects who were included in this study. Participants’ weights were measured with light indoor clothing, and their heights were measured with no shoes. BMI was then calculated as weight in kilograms divided by height in meters squared. Blood pressure was measured thrice with the participants in the sitting position after 5 min of rest.Blood samples were collected from all participants following an overnight fasting for at least 12 hours and detected rapidly. Serum biochemical parameters, including FPG, TG, total cholesterol (TC), low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol (HDL-C), and uric acid, were determined with a biochemical autoanalyzer . TyG-BMI was calculated according to the reference . White bt-test, one-way ANOVA, or chi-square test. A binary logistic regression analysis was conducted to explore the independent risk factors for NSCLC. Moreover, we performed a receiver operating characteristic curve (ROC) analysis to evaluate the ability of TyG-BMI to predict NSCLC. The results were considered statistically significant at a two-tailed P-value of < 0.05.All statistics in the study were performed with the SPSS 18.0 statistical software. The demographic and clinical characteristics of the participants are presented as mean (standard deviation) or percentage (numbers). Differences between or among groups were compared by Student’s P< 0.05). However, no significant difference in age, sex, family history of lung cancer, and blood pressure was observed between the two groups. The patients with NSCLC had high TyG-BMI than the healthy controls in both men  and women .The clinical characteristics of all the participants are described in P < 0.001].We performed a binary logistic regression analysis of TyG-BMI and NSCLC risk. In the unadjusted model, TyG-BMI was positively correlated with NSCLC [odds ratio (OR) = 1.039; 95% confidence interval (CI) 1.034–1.044, P< 0.001) for smoking as a risk factor for NSCLC was higher than that for TyG-BMI. After adjusting for potential covariates including lipid profile, TyG-BMI  was still positively associated with NSCLC (P = 0.004) and women . Meanwhile, all the subjects were classified into tertiles according to TyG-BMI. The prevalence of NSCLC gradually increased as the TyG-BMI tertiles increased. The prevalence of NSCLC in participants in the high TyG-BMI tertiles was 60.46%, which showed a nearly fivefold increase compared with that in the low tertiles , the squamous cell carcinoma group (n = 66), and the other type group (n = 14). In addition, the patients with NSCLC were also divided into three groups: Tis (n = 72), TNM I (n = 237), and TNM II-IV (n = 168) according to tumor-node-metastasis (TNM) stage. There were no differences in TyG-BMI according to pathological  or TNM stage .According to the pathological stage, the patients with NSCLC were divided into the adenocarcinoma group (P< 0.001) AUROC. These results indicated that TyG-BMI might be regarded as an optimal marker for predicting the occurrence of NSCLC.In the present study, we observed a strong and positive correlation between TyG-BMI and NSCLC risk even after controlling for confounding factors. However, there were no significant differences in the TyG-BMI levels of patients with different pathological or TNM stages. Moreover, TyG-BMI may be a simple and effective method for predicting incident NSCLC in Chinese adults.Lung cancer is the major cause of both the incidence and mortality of all cancers in China . UnfortuAlthough the mechanism involved in the link between NSCLC and TyG-BMI is poorly understood, IR may be involved in this relationship. On the one hand, hyperinsulinemia, which is a hallmark of IR, may contribute to the development of cancer because of the oncogenic potential of insulin by increasing the bioactivity of insulin-like growth factor I (IGF-I), enhancing growth factor-dependent cell proliferation, and/or directly affecting cell metabolism , 30. FurSeveral limitations may exist in our study. First, this was a case-control study conducted to investigate the relationship between TyG-BMI and NSCLC. However, a longitudinal study is more convincing than a case control study. Second, a questionnaire was not delivered to collect information such as environmental pollution and lifestyle. Moreover, information about secondhand smoke and radiation to the chest has not been available in this study. By adjustment of multivariate factors, some important variables were missing. Third, since the study participants came from a single hospital, the generalizability of our study to the general population is uncertain.TyG-BMI is positively associated with NSCLC and a valuable marker for predicting the risk of NSCLC. This marker is easily calculated from routine laboratory data and anthropometric measurements, and we suggest the possibility of applying TyG-BMI to identify individuals at high risk of NSCLC in epidemiological surveys. Certainly, further prospective large-scale multicenter studies will be needed to confirm our results in the future.The original contributions presented in the study are included in the article/supplementary material, further inquiries can be directed to the corresponding author/s.The studies involving human participants were reviewed and approved by the Human Research Ethics Committee of 3201 Hospital. The patients/participants provided their written informed consent to participate in this study.FW and ZY participated in the study design, wrote and modified the manuscript, and prepared tables and figures. FW, THe, GW, and THa were involved in the conduct of the study and data collection. FW and THe made contributions to data analysis and results interpretation. All authors contributed to the article and approved the submitted version.


Previous research shows that depression and personality are independently associated with self- and informant-reports of the ability to perform instrumental activities of daily living (IADLs). However, less is known about the association between depression and personality and performance-based measures of IADLs. We aimed to determine how depression and personality predict self-and informant-reports of IADL compared to performance-based measures of IADLs in a sample of older adults with normal cognition (NC) and Mild Cognitive Impairment (MCI).n = 235), or a diagnosis of MCI (n = 150), aged between 76 and 99-years from the Sydney Memory and Ageing Study. Participants underwent comprehensive neuropsychological and clinical assessments to determine global cognition and clinical diagnoses. Personality traits were measured by the NEO Five-Factor Inventory (NEO-FFI) and depression by the Geriatric Depression Scale (GDS). Subjective IADLs were self- and informant-reported Bayer Activities of Daily Living (B-ADL) scales and objective IADL was the Sydney Test of Activities of Daily Living in Memory Disorders (STAM). Linear regressions examined the relationship between depression and personality and the three types of IADL measures, controlling for all covariates and global cognition.Participants consisted of 385 older adults with NC . Informant-reported IADL was strongly associated with both global cognition and participants’ GDS scores. STAM scores were not associated with participants’ GDS or NEO-FFI scores; instead, they were predicted by demographics and global cognition.These results suggest that performance-based measures of IADL may provide more objective and reliable insight into an individual’s underlying functional ability and are less impacted by the participants’ mood and personality compared to subjectively reported IADL. We argue that performance-based IADL measures are preferable when trying to accurately assess everyday functional ability and its relationship to cognitive status. Where performance-based measures are not available , informant ratings should be sought as they are less influenced by the participant’s personality and mood compared to self-reports. The cornerstone of functional independence among older adults is an intact ability to perform necessary activities of daily living (ADL). The loss of independence in these activities is a key factor affecting the quality of life in individuals with dementia and their caregivers . ImpairmCurrently, the most common method for assessing IADL is self- or informant-  reported questionnaires , which aTo provide a more objective alternative to subjective self- and informant-reported IADL, performance-based measurements have been developed . PerformWhile some studies have examined the association between personality and self-report vs. performance-based IADL , to our The present study reports data from participants in the Sydney Memory and Ageing Study (MAS), a longitudinal study of community-dwelling older adults aged 70–90 years that began in 2005 . Of the Every 2 years, MAS participants undertook a detailed assessment with a trained research assistant during which they completed a comprehensive neuropsychological test battery, medical history, medical exam, and a series of questionnaires. Clinical diagnoses were made at each by an expert consensus panel who considered all available neuropsychological, clinical, and imaging data. At a 6-year follow-up, MCI was diagnosed using international consensus criteria , and demn = 38), as such a diagnosis precluded administration of both the self-report and the performance-based IADL measures, and a non-English speaking background , as cultural and linguistic variables, can bias standardized neuropsychological test results  of contact per week.For the present study, data from the 6-year follow-up are considered as this was the first time the performance-based assessment of IADL was administered. Of the 708 participants from the original MAS baseline sample included in the 6-year follow-up, there were 478 that completed the performance-based IADL measure. For the present study, further exclusion criteria were a consensus diagnosis of dementia at 6-year follow-up .participant have difficulty managing his/her medications?” to “Do you have difficulties managing your medications?” In this way, a direct comparison of participants’ and informants’ subjective appraisal of the same everyday activities could be captured while avoiding discrepancies between item phrasing or functional domains across measures. The modified self-report Bayer-IADL also takes on average 5 min to complete and is comprised of the same 25 items as the original Bayer-IADL   was origThe Sydney Test of Activities of daily living in Memory disorders (STAM)  is a perGlobal cognition composite scores were based on participants’ scores on a comprehensive neuropsychological test battery comprised of 10 tests that measured the domains of attention, language, executive function, visuospatial ability, memory, and verbal memory. Global cognition composite scores are presented as standardized z-scores and were derived as follows: Raw neuropsychological test scores were first converted to z-scores using the means and standard deviations (SDs) of a reference group comprised of 723 MAS participants from baseline that were classified as cognitively healthy . Composite domain scores were formed by averaging the z-scores of the component tests. Global cognition scores at each wave were calculated by averaging the domain scores. Global Cognition scores were standardized against the mean and SD  of the baseline reference group. More details about how cognitive domain and global cognition scores were calculated, and which tests comprised each cognitive domain, can be found in The short form of the Geriatric Depression Scale (GDS)  was admiCovariates included basic demographics of age, sex, and education. Medical covariates of interest comprised self-reported arthritis and vision impairment, which we transformed into a composite variable given both impairments have been shown to significantly impact participants’ ability to complete performance-based measures of IADL . Additio10), to improve normality and linearity, and univariate outliers were Windsorized. As analyses for both the raw and the transformed STAM and informant-report Bayer-IADL variables produced equivalent results, the raw data are listed in the table for ease of interpretation, but the transformed variables were used in analyses. Correlational analyses evaluated the relationship between participant-reported Bayer-IADL, informant-reported Bayer-IADL, and performance-based STAM scores.Prior to analyses, all variables were screened for violations of the assumptions associated with univariate and multivariate tests. Both STAM and informant-reported Bayer-IADL scores were non-normally distributed; to avoid potentially inflating α, these scores were transformed ; Step 2 additionally included participants’ Global Cognition composite score; and Step 3 additionally included participants’ depression (GDS) and personality  scores. We ran additional post-hoc analyses to determine whether diagnostic status  impacted the pattern of results. To do this, we ran the same series of hierarchical regressions, using the same steps and covariates outlined above, separately for the two groups.Three hierarchical linear regressions were run to determine the predictive ability of participants’ depression and personality traits on self-report, informant-report, and performance-based IADL scores, over and above the variance assumed by participant demographics, and medical covariates, and global cognitive function. For each of the three IADL outcome measures, a three-step hierarchical regression model was run in the same order. Step 1 always included participants’ demographics  and medical comorbidities , and stratified by diagnostic group . On average, participants were approximately 83 years old, were more often female (56%), and had just over 12 years of education. There was a low rate of depressive symptoms in the total sample, and participants self-reported more conscientiousness and openness compared to neuroticism. Group-level differences in participant characteristics for those with NC vs. MCI emerged for several test variables. Compared with the NC participants, those with MCI were older and had higher CVD risk scores, significantly lower global cognition scores, and openness scores. In terms of outcome variables, participants with MCI had significantly higher (worse) self- and informant-reported IADL and significantly lower (worse) performance-based IADL scores.r = 0.192, p < 0.001, N = 385). Conversely, performance-based IADL scores were significantly, and negatively, correlated with both self-  and informant-reported IADL . However, it is important to note that higher scores on the Bayer-IADL are indicative of worse IADL function whereas higher scores on the STAM indicate better IADL function. In sum, the strongest correlation to emerge was between informant-reported Bayer-IADL and STAM scores. Next, informant-reported, and participant-reported, Bayer-IADL scores emerged as significantly, but weakly, correlated (r < 2), as were participant-reported Bayer-IADL and STAM scores, which showed the weakest relationship among the three dependent variables.Self-reported IADL scores were positively correlated with informant-reported scores, such that participants who reported more IADL difficulty also had informants who reported more IADL difficulty  = 2.24, p = 0.039, and accounted for 3.7% of the variance in self-report IADL scores. Introducing the cognitive variables at step two contributed 2.8% of additional variance to the model, which was statistically significant, F = 10.43, p = 0.001. In step three, the addition of the depression and personality variables explained an additional 22.4% of the variance in self-report IADL, which was highly significant, F = 27.06, p < 0.001. Specifically, higher GDS and neuroticism scores, and lower conscientiousness scores, were related to higher  self-reported IADL scores, suggesting participants’ appraisals of their own functional ability were influenced by depressive symptoms and certain personality traits, over and above demographics, medical covariates, and global cognition.F = 5.87, p < 0.001, and accounted for 9.2% of the variance in informant-reported IADL. The addition of global cognition in step two explained an additional 4.7% of the variance in scores, which was highly significant, F = 18.85, p < 0.001. In step three, participants’ depression and personality scores accounted for an additional 7.5% of the total model variance, over and above demographic, medical, and cognitive variables. This additional variance was statistically significant, F = 8.21, p < 0.001, and largely driven by participants’ GDS scores, which uniquely explained 6% of the variation in informant-report IADL scores. These results suggest that while informants’ appraisals of participants’ functional ability are influenced by some variables expected to impact functional ability , they are also significantly impacted by dynamic participant characteristics like depression.F = 17.29, p < 0.001, and accounted for 23.7% of the variance in performance-based IADL scores. Introducing global cognition at step two explained an additional 23% of the variation in performance-based IADL and this change in R2 was highly significant, F = 148.36, p < 0.001, with global cognition scores alone explaining an additional 12% of the variance, over and above age, sex, and education and medical covariates. Interestingly, the addition of depression and personality in the final step did not contribute significantly to the final regression model, F = 0.28, p = 0.508. Together, these results suggest that scores on performance-based measures of IADLs are influenced most by participant characteristics like age, sex, education, and cognitive variables, as opposed to current depression or certain personality traits.p < 0.001; MCI: β = 0.392, p < 0.001) and conscientiousness  remained significant for both groups. However, the significant effect of global cognition  and neuroticism  appear to be driven mostly by NC participants. p = 0.008) where the effects of global cognition  and GDS  were driven by the MCI group. Openness also emerged as significant for MCI participants , where this was not significant in the original model. Finally, p < 0.001; MCI: β = 0.583, p < 0.001), though the association with education appears to be driven by the NC group, only .Finally, to explore whether patterns of association differed by diagnostic status , we re-ran our three hierarchical regressions, using the same steps and covariates as before, separately for the two groups. These results are presented in Post-hoc analyses considering diagnostic groups revealed that in some instances associations with the full sample analysis held  in other cases differences were driven by one group over the other . However, given we were most interested in understanding how these variables across the predementia spectrum influence different measures of functional ability, we focus our attention on the group level analyses.This study examined the associations between measures of cognitive function, depressive symptoms, and personality traits and different methods of assessing IADL in a community-dwelling older sample, controlling for demographics and potential medical confounders. When considering the total sample, we found that self-reported worse IADL was associated with worse global cognition scores, depressive symptoms, higher scores on neuroticism, and lower scores on conscientiousness. Worse informant-reported IADL function was also associated with worse global cognition scores and increased depression scores but was not associated with participants’ personality traits. Finally, performance-based IADL scores were associated with age, sex, education, and global cognition, but were not associated with depression or personality traits in any significant way. In addition, the three measures of IADL were only weakly correlated, which may reflect how each measure is variably influenced by demographics, mood, personality traits, and cognition. Our findings that self-reported IADL impairment is significantly associated with higher neuroticism and lower conscientiousness align with other previous reports . Given tOur findings further revealed that depression was significantly associated with worse subjective IADL ratings reported by both the participant and their informant, suggesting that individuals with depressive symptoms, and their informants, may tend to overreport IADL impairments. These results support previous research showing depressive symptoms predict worse self-reported IADL performance over time . HoweverThe finding that depressive symptoms were not associated with IADL function as measured by an objective performance-based measure favors the hypothesis that depressive symptoms may be related to overreporting of IADL impairment rather than actual functional decline. One explanation for this relationship is that participants experiencing depressive symptoms may more easily recollect negative instances when they could not perform daily tasks. This is supported by research on the relationship between mood and memory . HoweverInterestingly, all three measures of IADL were significantly associated with global cognition. However, this association was strongest for objective performance-based IADL ability in comparison to subjectively reported IADL. Nearly 22% of the total variance in performance-based IADL scores was predicted by global cognition compared to less than 2% for self-report and less than 4% for informant-report. Again, this may be due to the impact of depressive symptoms and personality traits on subjective impressions of IADL ability. Taken together, our results suggest that performance-based measures are more reflective of the individual’s cognitive status compared to performance-based measures. This is consistent with previous research which has demonstrated that performance-based IADL measures may be more sensitive in discriminating between cognitive status .Strengths of our study are the relatively large and well-characterized sample, expert consensus clinical diagnosis of NC vs. MCI, the inclusion of important medical covariates, and the three types of IADL measures. To our knowledge, subjective self- and informant-reported IADL and performance-based IADL have not been examined together with depression and personality in one cohort. This study has certain limitations. Firstly, the data analyzed are cross-sectional and provide limited information on whether depressive symptoms are the antecedent or consequences of functional impairment in IADL. Further longitudinal studies should endeavor to explore this issue, particularly relating to performance-based IADL measures. We do not include measures of informant-reported depression, personality, or perceived burden, which may also impact their subjective reports of participants’ IADL ability. A final limitation is that this study only examined individuals with normal cognition or MCI. Thus, the findings do not extend to individuals with dementia. As dementia can have a long prodromal period, future research should look at whether the relationships reported here are similar or different for persons with mild or moderate dementia diagnoses.In sum, while self-reported IADL function was significantly associated with the participant’s current level of global cognition it was more strongly associated with depressive symptoms and personality traits. Informant-reported IADL was also influenced by depressive symptoms but was not impacted by personality traits and was strongly associated with global cognition. Finally, performance-based IADL scores were not significantly associated with the participant’s depression and personality traits; instead, they were mostly accounted for by the participant’s age, sex, education, and global cognition—all variables known to be associated with functional ability in older adults. We argue that performance-based IADL measures are preferable when trying to accurately assess everyday functional ability and its relationship to cognitive status. Where performance-based measures are not available , informant ratings should be sought as they are less influenced by the participant’s personality and mood compared to self-reports.ChebaData@unsw.edu.au, or via KN, k.numbers@unsw.edu.au.The terms of consent for research participation stipulate that an individual’s data can only be shared outside of the MAS investigators group if the group has reviewed and approved the proposed secondary use of the data. This consent applies regardless of whether data have been de-identified. Access is mediated via a standardised request process managed by the CHeBA Research Bank, who can be contacted at The studies involving human participants were reviewed and approved by the University of New South Wales Human Research Ethics Committee. The patients/participants provided their written informed consent to participate in this study.KN designed this study, wrote this manuscript, completed all analyses, and prepared this manuscript for submission. SJ, HB, PS, and BD provided statistical, neuropsychological, and medical guidance, and reviewed this manuscript and revisions. SR provided detailed feedback and guidance at each step of design and manuscript drafting as senior author. All authors contributed to the article and approved the submitted version.HB was advisory board member or consultant to Biogen, Nutricia, Roche and Skin2Synapse. He was Medical/Clinical Advisory Board member for Montefiore Homes and Cranbrook Care. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.


Having played important roles in human growth and development, livestock animals are regarded as integral parts of society. However, industrialization has depleted natural resources and exacerbated climate change worldwide, spurring the emergence of various diseases that reduce livestock productivity. Meanwhile, a growing human population demands sufficient food to meet their needs, necessitating innovations in veterinary sciences that increase productivity both quantitatively and qualitatively. We have been able to address various challenges facing veterinary and farm systems with new scientific and technological advances, which might open new opportunities for research. Recent breakthroughs in multi-omics platforms have produced a wealth of genetic and genomic data for livestock that must be converted into knowledge for breeding, disease prevention and management, productivity, and sustainability. Vetinformatics is regarded as a new bioinformatics research concept or approach that is revolutionizing the field of veterinary science. It employs an interdisciplinary approach to understand the complex molecular mechanisms of animal systems in order to expedite veterinary research, ensuring food and nutritional security. This review article highlights the background, recent advances, challenges, opportunities, and application of vetinformatics for quality veterinary services. Livestock animals are an essential part of our life. Science-led innovation in veterinary research that benefits both people and animals as individuals and populations is crucial to maintaining public health , 2. ThisThe functioning of livestock systems is an area of active, ongoing research. Advancements in mathematical science, statistical methods, computer science, and information technology help biologists learn about biological systems quantitatively and qualitatively . ComputeDue to significant improvements in the crystallographic determination of protein structures , proteinNeedleman and Wunsch created the first dynamic programming method for pairwise protein sequence alignment in 1978 . Since tIn veterinary science, the livestock production system is a complex process that has three interconnected basic components: animal biology, the environment, and management techniques . Therefohttps://www.frontiersin.org/research-topics/33198/vetinformatics-an-insight-for-decoding-livestock-systems-through-in-silico-biology).Vetinformatics is associated with the disciplines of veterinary sciences, basic sciences, and engineering; these disciplines provide infrastructure and an interdisciplinary nature to vetinformatics , 33, 34.https://www.veterinaryirelandjournal.com/ucd-research/165-how-omics-are-contributing-to-sustainable-animal-production; accessed on 14/7/2022). Vetinformatics' aim is to decode the enormous quantity of multi-omics data produced by high-throughput technologies, structural and functional characterizations of key genes and proteins, and visualizations of key components linked with livestock productivity and sustainability . In the field of genomics, annotating genomes through MAKER is convenient and easy. Genomes of eukaryotes and prokaryotes can be annotated independently and genome databases can be created using it. It is designed to identify repeats, align ESTs and proteins with the genomes, and produce ab-initio gene predictions . They assembled the 35 million sequence reads to produce an improved assembly of 2.86 billion base pairs. Numerous computational tools can be used to further evaluate sequenced genomes. Several pipelines, resources, and software are available for computational assembly and study of the genome. Recent functional annotation of three domestic animal genomes  provides a useful resource for livestock research  and microRNAs (miRNA) play vital roles in gene regulation . Recent Metagenomics allows for direct access to genetic information of whole communities by utilizing a variety of genomic technologies and computational approaches . It presin silico analysis, the study investigated transcription start sites and promoter regions of olfactory receptors in cattle, identifying five candidate motifs  important in gene regulation , MUSCLE (https://www.ebi.ac.uk/Tools/msa/muscle/), and T-Coffee (https://www.ebi.ac.uk/Tools/msa/tcoffee/) to perform multiple sequence alignment and building a phylogenetic tree using different methods. There has been increasing interest in reconstructing phylogenetic trees in biological science, and questions are being raised regarding the degree of confidence one should place in any given phylogenetic tree. The concept of bootstrapping and jackknifing was introduced to construct error-free phylogenetic tree (https://www.megasoftware.net/web_help_11/Bootstrap_Test_of_Phylogeny.htm). The Interactive Tree Of Life, i.e., iTOL (https://itol.embl.de/) and Tree View are highly cited tools facilitating phylogenetic tree visualization , Animal QTLdb , NAGRP , Ensembl (https://asia.ensembl.org/index.html), and UCSC (https://genome.ucsc.edu/) are valuable resources (https://gatk.broadinstitute.org/hc/en-us). Uemoto et al. identified six significant quantitative trait loci for immune-related traits in pigs affected by mycoplasma pneumonia of swine using GWAS, revealing novel insights into the genomic elements influencing pig production, respiratory illness, and immune-related traits . Pan et al. predicted the cow milk 3D structures of αs1-CA and β-CA using I-TASSER to understand its dynamics  via the screening of 97,999 natural compounds from the ZINC database  grant funded by the Korean government (MSIT) (NRF-2022R1A2C1005830).The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.


Accurate glioma subtype classification is critical for the treatment management of patients with brain tumors. Developing an automatically computer-aided algorithm for glioma subtype classification is challenging due to many factors. One of the difficulties is the label constraint. Specifically, each case is simply labeled the glioma subtype without precise annotations of lesion regions information. In this paper, we propose a novel hybrid fully convolutional neural network (CNN)-based method for glioma subtype classification using both whole slide imaging (WSI) and multiparametric magnetic resonance imagings (mpMRIs). It is comprised of two methods: a WSI-based method and a mpMRIs-based method. For the WSI-based method, we categorize the glioma subtype using a 2D CNN on WSIs. To overcome the label constraint issue, we extract the truly representative patches for the glioma subtype classification in a weakly supervised fashion. For the mpMRIs-based method, we develop a 3D CNN-based method by analyzing the mpMRIs. The mpMRIs-based method consists of brain tumor segmentation and classification. Finally, to enhance the robustness of the predictions, we fuse the WSI-based and mpMRIs-based results guided by a confidence index. The experimental results on the validation dataset in the competition of CPM-RadPath 2020 show the comprehensive judgments from both two modalities can achieve better performance than the ones by solely using WSI or mpMRIs. Furthermore, our result using the proposed method ranks the third place in the CPM-RadPath 2020 in the testing phase. The proposed method demonstrates a competitive performance, which is creditable to the success of weakly supervised approach and the strategy of label agreement from multi-modality data. In 2011–2015, there are 23 out of 100,000 population diagnosed with brain tumors in the US2. Prior to 2016, World Health Organization (WHO) categorizes the CNS gliomas into grades I–IV based on the histological features of a heterogeneous population of the tumor3. However, a new brain tumor classification criterion was released from the WHO in 2016. According to the new criterion, the tumor classification is determined based on both phenotypic and genotypic information4. There are many glioma subtypes: diffuse astrocytoma, isocitrate dehydrogenase (IDH)-mutant/-wildtype, anaplastic astrocytoma IDH-mutant/-wildtype, oligodendroglioma, IDH-mutant and 1p/19q-codeleted, glioblastoma, IDH-mutant/-wildtype, etc. The prognosis of a patient with brain tumors is highly related to the tumor grade2. In general, patients with higher-grade gliomas have a less survival period. Especially, for patients with glioblastoma (GBM), the median survival period still remains 12–16 months, even with treatment advancement5. Consequently, an accurate and robust glioma subtype prediction provides a valuable guide for diagnosis and treatment management. Conventionally, brain tumor diagnosis or grading is performed by pathologists, who examine tissue sections fixed on glass slides under a light microscope. Yet, the manual diagnosis/grading process is time-consuming and susceptible to human errors. Therefore, computer-aided brain tumor subtype classification is highly desired.Brain tumors, originating in the glial cells, are cancerous masses in the central nervous system (CNS)6. Digital pathology has become increasingly common because of the rich context information on the WSI. There are extensive studies on tumor subtype classification in the literature: Kothari et al. utilize a multi-class model for histological classification7. Chang et al. use the spatial pyramid matching framework (SPM) with a linear Support Vector Machine (SVM) classifier to classify glioblastoma multiforme (GBM)8. A hybrid machine learning method using SVM, random forest (RF), and neural network (NN) is proposed for glioma grading based on the WSI9. Barker et al. exploit an elastic net for brain tumor type classification10. However, a common limitation of these conventional machine learning methods is feature extraction, which requires professional clinical background and computer vision knowledge. In recent years, deep learning (DL)-based approaches have shown superior performance, and have been widely applied in many domains, e.g., computer vision11, medical image analysis13, and natural language processing (NLP)14. The deep learning-based methods is also adopted for glioma classification based on WSI15 and for glioma grading17.Prior to 2016, digital pathology images are the primary sources for the glioma subtype classification. Digital pathology is the digitized process of whole slide images (WSI) transforming into high-resolution images. apply a SVM-based method to classify tumor type on MRI18. In the paper, they first extract radiological features, e.g., tumor shape and intensity characteristics. They then apply feature selection using a SVM with recursive feature elimination. Finally, they perform the tumor classification using another SVM. In addition, a hybrid method using a SVM and k-nearest neighbour classifiers (named as SVM-KNN) is also utilized for brain cancer classification19. In Refs.21, Random Forest (RF)-based methods are used for tumor classification as well. Recently, CNN-based methods have been becoming prevalent for such tasks23. Sajjad et al. propose a deep learning-based method for multi-grade brain tumor classification24. Liu et al. present a multi-task CNN algorithm for joint segmentation and genotype prediction of brainstem gliomas25. Pei et al. utilize a 3D CNN-based method for brain tumor subtype classification, and achieve the state-of-the-art performance26.On the other hand, MRI is an alternative source for glioma grading because of the noninvasive property. The MRI-based approaches also provide promising results for glioma classification and grading. Zacharaki et al. propose CNN-based methods for tumor classification on WSI and MRI30. Kurc et al. investigate brain tumor classification using machine learning and deep learning on WSI and MRI31. The work of using both WSI and MRI in Refs.30 offers state-of-the-art performance. However, all the methods are fusion-based at the feature level. We argue that these methods undermine the priority of pathology in tumor classification, which conflicts with the criterion defined by the WHO. We should develop a computer-aided diagnosis system and should take pathological modality as the primary source for tumor classification.Unsurprisingly, a combination of pathology and radiology images provides more comprehensive context information than using a single modality alone. Ma et alTherefore, we propose a novel hybrid fully convolutional neural network (CNN)-based method for glioma subtype classification using both whole slide image (WSI) and multiparametric magnetic resonance image (mpMRIs). The proposed method primarily focuses on the WSI-based result while taking the mpMRIs-based result as the complementary reference to enhance the robustness.In this section, the proposed two approaches (the WSI-based approach and the mpMRIs-based approach) are elaborated. In addition, the label agreement strategy for fusing the prediction is also covered.Figure 32, the classification task is still challenging because of the small number of cases and the label constrain issue. The label of the WSI is given, however, the precise lesion region information is missing. The issue becomes worse when considering the massive size of WSI. The inexact labeling in a weakly supervised learning task results in inaccurate samples in the training process. Extracting representative patches is of importance for the task. To overcome the label constrain issue, we extract multiple patches according to the intensity distribution, and assign the corresponding label, as shown in Fig. 33. Subsequently, the trained CNN model is used to extract the convolutional representations (deep features) for each sampling patch. To reduce the impact of non-representative samples in each class, several prototypes for each category are selected by pair-wise similarity check. The extracted prototypes (e.g. 100 prototypes for each category in our experiment) are selected according to the similarity of intensity distribution. However, non-representative prototypes may also be collected because of the existence of irrelevant tissues such as lymphocytes, red blood cells, and mostly stroma, etc. In addition, astrocytoma and oligodendroglioma have similar morphological features and are commonly confounded diagnoses with large intraobserver variabilities35. Last, an expert intervention step is to screen out the non-representative prototypes further or re-assign to another category.Even the training data with paired image and classification label is available in the CPM-RadPath 2020 challengeS is computed by pair-wise comparison of patches using cosine similarity, and each entity ith or jth sampling patch , turn into probabilities indicating the confidence score for each glioma subtype. While for the MRI-based approach, the prediction probability for each class can be retrieved directly from the CNN classification network. According to the guideline of CNS glioma classification defined by WHO, histopathology information is the primary image source for the glioma subtype classification. Thus, we primarily consider the WSI-based result as the final prediction, but also take the mpMRIs-based result as a complementary reference when the confidence index of the WSI-based result is less than the pre-defined threshold, 45 and Computational Precision Medicine: Radiology-Pathology Challenge on brain tumor classification (CPM-RadPath) 202031. Approval was granted on the grounds of existing datasets. Informed consent was obtained from all of the patients in this study. All methods were carried out in accordance with relevant guidelines and regulations. Ethical approval for the use of these data was obtained from the ethics committee of University of Pittsburgh.In this study, the MRI images and pathology images sourced from two pubic dataset: multimodal Brain Tumor Segmentation Challenge (BraTS) 2020The BraTS 2020 training data contains 369 cases including 76 low-glioma grade (LGG) patients and 293 high-glioma grade (HGG) patients. For each case, there are multiparametric MRIs (mpMRIs) and the corresponding ground truths of brain tumors. The mpMRIs include T1-weighted MRI (T1), T1-weighted MRI with contrast enhancement (T1ce), T2-weighted MRI (T2), and T2-weighted MRI with fluid-attenuated inversion recovery (T2-FLAIR). Each modality of each case has a size of IDH-mutant (A), oligodendroblioma, 1p/19q codeltion (O), and glioblastoma and diffuse astrocytic glioma with molecular features of glioblastoma, IDH-wildtype (G), respectively. In addition, there are 35 and 73 cases for the validation and testing sets in the CPM-RadPath 2020 challenge, respectively. It notices that the challenge organizer privately owns the ground truth of the glioma subtype of the validation and testing data. In the validation phase, participants submit the prediction results to the challenge for online evaluating the algorithm. However, participants are only allowed to submit the algorithm wrapped in a Docker container in the testing phase, and the organizer executes the algorithm for final ranking.For the data from CPM-RadPath 2020, the training dataset is comprised of 221 cases with paired radiology and digital pathology images. Within the 221 cases, there are 54, 34, and 133 cases for lower grade astrocytoma, Three metrics are utilized for performance evaluation in the challenge of CPM-RadPath 2020 for glioma subtype classification, which are micro-F1, Cohen’s Kappa Coefficient, and balanced accuracy. In the tasks of multi-class classification, the micro-F1 is equivalent to the overall accuracy, as Eq. .4\documepo is the relative observed agreement among raters, and pe is the hypothetical probability of chance. Lastly, the balanced accuracy computes the average of the proportion corrects of each class individually, which is formulated in Eq. , enhancing tumor (ET), and necrosis or non-enhancing tumor (NCR/NET). The segmentation results of three targeted tumor subregions are shown in Fig. 33 to train the relations between tumor morphology and glioma subtypes.On the other hand, for the MRI-based approach, a 3D CNN model of ResUNetIt notes that the CPM-RadPath 2020 has identical datasets as CPM-RadPath 2019. Since the glioma subtype of ground truth for each case in the testing set from the challenge of CPM-RadPath 2020 is not publicly available, in our experiments, the performance on the validation set from the challenge is focused for evaluation and comparison.Ct, is empirically set to be 0.6 in our experiment. The comparison shows a promising result that a label fusion-based predictions using the proposed method outperform the ones from single approach.The performance of the two approaches and the scheme of label agreement is listed in Table In addition, we also compare our result to the other top-ranked teams in the validation phase, as shown in Table From the pathological perspective, the morphologies of glioma subtypes are distinct. As it can be observed in Fig. Figure However, misclassification also occurs. In the experiment, there are another two cases misinterpreted, as shown in Fig. Though the proposed method produces a competitive result, there are some limitations. First, we use both WSI and mpMRIs for the classification. To achieve the best result, we assume that an accurate brain tumor subregion results in a good classification. In doing so, we use an extra dataset from BraTS 2020, which limits its application. Second, the proposed method is sensitive to some empirical parameters, such as the threshold of confidence index, the number of extracting patches, etc. Third, the relatively small size of experimental data is a drawback, which widely exists in deep learning-based methods. Forth, the proposed method requires a qualified professional or expert intervention to screen out the non-representative prototypes.In this study, we propose a novel hybrid fully convolutional neural network (CNN)-based method for glioma subtype classification using both whole slide image (WSI) and multiparametric magnetic resonance images (mpMRIs). It is comprised of two methods: a WSI-based method and a mpMRIs-based method. For the WSI-based method, we categorize the glioma subtype using a 2D CNN on WSIs. For the mpMRI-based method, we also develop a 3D CNN-based method by analyzing the mpMRI. The mpMRIs-based method consists of brain tumor segmentation and classification. We classify the glioma subtype primarily on WSI-based results with the guidance of the mpMRIs-based prediction when the confidence index of the WSI-based result is less than the pre-defined threshold. The experimental results show that the final label fusion-based predictions achieve a superior result and offer a competitive performance.


Given the high risk of contracting a healthcare-associated infection in long-term care facilities, infection prevention and control are essential for the quality of care and safety of residents and staff. To develop more effective infection prevention and control interventions in long-term care facilities, it is important to assess the cost-effectiveness and cost-benefit of existing interventions. There are only a few reviews on this subject, but these are not recent and most do not perform an economic evaluation. Moreover, none uses a discounting approach which limits inter-study comparison. To address these gaps, we will conduct a systematic review of economic evaluations related to healthcare-associated infection prevention and control in long-term care facilities using a discounting approach.We will query MEDLINE, Embase, Web of Science, Cochrane, CINAHL, EconLit, JSTOR, and Scopus, as well as the gray literature databases CORDIS and ProQuest. We will include quantitative studies that evaluate four clinical best practices associated with infection prevention and control  and use at least one of five economic analyses . Primary outcomes will include net cost savings, incremental cost-effectiveness ratio, incremental cost per quality-adjusted life year, and incremental cost per disability-adjusted life year. Two co-authors will independently screen and select articles, extract data, and assess the quality of selected articles using the Scottish Intercollegiate Guidelines Network criteria, the Economic Evaluation criteria, and the Cochrane criteria for economic evaluation. Extracted data will be synthesized, and values will be adjusted to 2022 Canadian dollars using the discount rates of 3%, 5%, and 8%.Information obtained through this systematic review may help researchers and policy makers make more efficient use of limited healthcare resources to ensure the safety and quality of long-term care.Research registry ID: reviewregistry1210.The online version contains supplementary material available at 10.1186/s13643-022-02128-7. Healthcare-associated infections (HCAIs) present a public health concern as they generate extra treatment costs, reduce quality of life, and increase the risk of morbidity and mortality –3. HCAIsLTCF residents are particularly vulnerable to HCAIs due to host risk factors such as multiple comorbidities and age-associated changes in immunity, as well as risks inherent in living in congregate environments . Colonizstreptococcus. Other common culprits of outbreaks include noroviruses, Salmonella sp., Clostridium difficile, Escherichia coli, Streptococcus pneumoniae, and coronaviruses . Al. Al10]. We will only include economic analyses of the four CBPs associated with HCAI prevention and control: (1) hand hygiene, (2) hygiene and sanitation, (3) screening on admission, and (4) basic and additional precautions. Studies that evaluate any practice(s) other than these four CBPs will be excluded.The following study designs will be included: controlled clinical trials, randomized controlled trials (RCTs), cohort studies, longitudinal studies, follow-up studies, prospective studies, retrospective studies, cross-sectional studies, studies based on mathematical/statistical modelling, and simulations. Qualitative studies, systematic reviews, meta-analyses, meta-syntheses, and scoping reviews will be excluded.Outcomes will include quantitative studies using CMA, CEA, CUA, CBA, or CCA, as well as studies using any combination of these analyses. Technological assessments, purely clinical studies, and pharmacological studies will be excluded. We will adopt the LTCF as the analytical frame and 1 year as the time horizon. The following measures of cost-effectiveness will be used: net cost savings (savings-costs), incremental cost-effectiveness ratio (ICER=effectiveness/costs), incremental cost per QALY, incremental cost per disability-adjusted life year (DALY), and incremental benefit-cost ratio (IBCR=savings/costs).This systematic review protocol has been registered in Research Registry. The methods were developed in accordance with the Preferred Reporting Items for Systematic Review and Meta-Analysis Protocols (PRISMA-P) 2015 statement. A PRISMA-P checklist is included as Supplementary File Scientific articles will be retrieved via iterative exploratory searches in eight electronic databases: MEDLINE via Ovid, Embase, Web of Science, Cochrane, CINAHL, EconLit, JSTOR, and Scopus. We will also query the gray literature databases CORDIS and ProQuest. Database searches will be performed using the Boolean operators “AND” and “OR.” We will only include articles written in English or French and published between 1992 and 2022.All co-authors, including two IPC program specialists , contributed to the determination of keywords. Search strategies were established in collaboration between all co-authors including an experienced librarian (CS) at the Saint-Jérôme campus of the Université du Québec en Outaouais. A CINAHL search strategy is presented in Table First, the research librarian will query the databases based on the established search strategies and create an Endnote database of retrieved articles. Duplicates will be identified and eliminated. All citations will be exported into the Rayyan web platform . To imprTo extract data from selected articles, we will create an Excel spreadsheet based on the Consolidated Health Economic Evaluation Reporting Standards (CHEERS) . We willCochrane Handbook for Systematic Reviews of Interventions, we will adhere to the Cochrane criteria for economic evaluation [We will assess the quality of selected articles by applying three tools that are commonly used to conduct economic evaluations. First, we will use the audit guidelines for economic evaluation studies recommended by the Scottish Intercollegiate Guidelines Network (SIGN) . Second,aluation . By emplaluation . The quaFor each intervention, we will tabulate the following parameters: costs, HCAI incidence reduction due to intervention, cost-effectiveness ratios, cost-utility ratios, and cost-benefit ratios. We will also report the year of calculation and the currency used.I2 statistic with a value of 85% or greater representing substantial heterogeneity [Economic evaluations are context and time sensitive since resource use and costs are contingent on the setting, clinical practice, and exchange rate, which can generate high heterogeneity . Therefoogeneity . Furtherogeneity . We willAll currencies will be converted into 2022 CAD . Based oThe Grading of Recommendations, Assessment, Development and Evaluations (GRADE) guidelines  will be Université du Québec en Outaouais (Project #2022-1883). The results of this review will be published in a peer-reviewed journal and presented at scientific conferences.This study does not require ethical approval as it will not use individual patient data. This systematic review is included in the research program “Investir en prevention et contrôle des infections: Investir en PCI.” This program has been accepted by the Research Ethics Committee of the This protocol lays the groundwork for a systematic review aimed at synthesizing the current evidence on the cost-effectiveness of HCAI prevention and control interventions using CBPs in LTCFs. Findings of our systematic review can provide researchers and policy makers with evidence-based information, potentially allowing them to make a more efficient use of limited healthcare resources to ensure the safety and quality of long-term care.One potential limitation of this systematic review is the exclusion of qualitative studies, purely clinical and pharmacological studies, and technological assessments. Another potential limitation is the consideration of only those interventions that use one or more of the four CBPs as defined by the theoretical framework. Furthermore, potential heterogeneity of extracted data may limit the generalizability of findings. Despite these limitations, our review will be the first to synthesize the existing knowledge on the cost-effectiveness of HCAI prevention and control in long-term care using a discounting approach. The application of three different tools to assess the quality of selected articles will enhance the robustness of our assessment. We will also maintain the rigor of our review by following the CHEERS checklist for data extraction and analyzing the data using the JBI's DRM and sensitivity analyses. Overall, the theoretical framework based on CBPs will guide us throughout all stages of the review, helping us maintain methodological congruence between the study’s objectives, data collection and analysis, and aggregation of results.Additional file 1. PRISMA-P 2015 Checklist.